Professor Amar Aggoun

Recent advances in camera technologies has led to the design of plenoptic cameras. This camera type can capture multiple images of the same scene using arrays of microlenses, where each microlens has a shifted location providing a separate view of the scene. Such a design results in a superior performance as compared to traditional cameras, enabling multi-view or multi-focal imaging captured in a single shot. However, currently available plenoptic cameras are limited in spatial resolution, which makes it difficult to use them in applications where sharpness or high resolution is key, such as the film industry. Our paper presents a novel light field hybrid super-resolution method that combines two classical super-resolution techniques for efficient application to plenoptic images. After this combination, we first segment the output hybrid super-resolution image into the objects of interest. Afterward, we apply sparse representation to super resolve the segmented image. This technique helps to improve the quality by decrease computations for light field images and extract significant features from the objects of interest. We demonstrate the gain achieved by the novel method as compared to the current relevant approaches in terms of both PSNR and SSIM for various enhanced spatial resolutions.

A new realisation of DPCM video signal/image processing that provides the designer with more flexibility in finding the best trade offbetween throughput rate and hardware cost is introduced. This is achieved by combining the digitserial computation with the DPCM video signal processing. The advantage of the proposed realisation is that the size of the memory used for multiplication can be reduced by a factor of at least 32 compared to 16 in the existing DPCM implementations.

The objective of this paper is to build and develop a software package for simulating an ultrasonic ranging system, in such a way that the data can be integrated in an optical scanning system. In achieving the objective the following aspects are investigated. First, the ultrasonic transducer is modelled. A new model for an ultrasonic transducer is developed. The transducer is decomposed based on its filtering and damping properties. Models for propagation medium and different targets are integrated into the simulation system. The Ranging System is simulated, using the proposed models. The simulated results are discussed by comparison with experimental measurements.

In this paper we propose a novel approach to use both motion and disparity information to compress 3D integral video sequences. The integral video sequence is decomposed into 8 viewpoint video sequences and a block search is performed to jointly exploit the motion and disparity redundancies to maximize the compression. An Evolutionary Strategy (ES) based search algorithm is used to reduce the complexity. Experimental results show that an ES based strategy can reduce the motion estimation complexity by 95%. ©2007 IEEE.

Plenoptic imaging enables a light-field to be captured by a single monocular objective lens and an array of micro lenses attached to an image sensor. Metric distances of the light-field's depth planes remain unapparent prior to acquisition. Recent research showed that sampled depth locations rely on the parameters of the system's optical components. This paper presents PlenoptiSign, which implements these findings as a Python software package to help assist in an experimental or prototyping stage of a plenoptic system.

A compression scheme for Omnidirectional Integral Image data is described which uses a three dimensional DCT to exploit the intra-sub-image correlation together with the horizontal and vertical inter-sub-image correlation, resulting in a very efficient de-correlation of the source intensity distribution. The nature of the recorded intensity distribution data with respect to redundancies present and the structure of the data representing the image object are investigated. A three dimensional scalar quantisation array is applied to the DCT coefficients, which are then entropy encoded by a Huffman-based coder. The results obtained after applying the 3D DCT based scheme to Oil data are presented and discussed, and compared with simulations produced using the JPEG scheme. © 2006 IEEE.

in this paper, application software devoted to simulate a 3-D integral imaging system (3-D camera) and produce static and animated 3-D autostereoscopic good quality integral images that are viewable without the need for special glasses is introduced. The resulting images are capable to provide the viewer with 3-D effect and parallax. A Human Machine Interface (HMI) is provided with the software to allow user to tune and set the parameter values of the required imaging systems and the required integral image characteristics. The software receives the instructions and the parameter values from the HMI, and imports the computergenerated 2-D scenes that are intended to be rendered as 3-D integral images. The integral imaging process that is implemented with the simulated camera is based on particular algorithms introduced for this purpose (e.g Displacement of Camera Target DCTarget and the integral imaging method of dividing the camera view volume DIVGL).

The fast growth of the world population associated with the ever-increasing need for food and the significant contribution of agriculture to anthropogenic global warming is driving the changes from conventional farming approaches to innovative and sustainable agriculture ones. One of these approaches is aquaculture which is founded on the principle of circular economy combining aquaculture and hydroponics in symbiose with aquaculture waste serving as nutrients for plant growth. Conventional Aquaponics has evolved to Aquaponics 4.0 with a fully automated and remote-controlled system for producing foods at an industrial scale. The implementation of the Internet of Things (IoT) and Artificial Intelligence (AI) could simplify farmers’ tasks with remote operations while allowing them to achieve automatic and precise control of inputs and outputs as well as to improve the overall efficiency of the system. This review focuses on the use of these smart technologies to analyze, monitor, and maintain good water quality and appropriate replenishment in Aquaponics systems. The identified research gap and future possible contributions in this area are also discussed.

By law, schools are required to protect the well-being of students against problems such as on-campus bullying and physical abuse. In the UK, a report by the Office for Education (OfE) showed 17% of young people had been bullied during 2017–2018. This problem continues to prevail with consequences including depression, anxiety, suicidal thoughts, and eating disorders. Additionally, recent evidence suggests this type of victimisation could intensify existing health complications. This study investigates the opportunities provided by Internet of Medical Things (IoMT) data towards next-generation safeguarding. A new model is developed based on blockchain technology to enable real-time intervention triggered by IoMT data that can be used to detect stressful events, e.g., when bullying takes place. The model utilises private permissioned blockchain to manage IoMT data to achieve quicker and better decision-making while revolutionising aspects related to compliance, double-entry, confidentiality, and privacy. The feasibility of the model and the interaction between the sensors and the blockchain was simulated. To facilitate a close approximation of an actual IoMT environment, we clustered and decomposed existing medical sensors to their attributes, including their function, for a variety of scenarios. Then, we demonstrated the performance and capabilities of the emulator under different loads of sensor-generated data. We argue to the suitability of this emulator for schools and medical centres to conduct feasibility studies to address sensor data with disruptive data processing and management technologies.

A new VLSI architecture for the computation of the three-dimensional discrete cosine transform (3D DCT) for compression of Integral 3D Images is proposed. The 3D DCT is decomposed into 1D DCTs computed in each of the three dimensions. The architecture is a parallel structure which computes an N×N×N-point DCT by computing N N×N 2D DCTs in parallel and feeding each of the computed 2D DCT coefficients into a final 1D DCT block. The architecture uses 5N

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3D imaging techniques have the potential to establish a future mass-market in the fields of entertainment and communications. Integral imaging, which can capture true 3D color images with only one camera, has been seen as the right technology to offer stress-free viewing to audiences of more than one person. Just like any digital video, 3D video sequences must also be compressed in order to make it suitable for consumer domain applications. However, ordinary compression techniques found in state-of-the-art video coding standards such as H.264, MPEG-4 and MPEG-2 are not capable of producing enough compression while preserving the 3D clues. Fortunately, a huge amount of redundancies can be found in an integral video sequence in terms of motion and disparity. This paper discusses a novel approach to use both motion and disparity information to compress 3D integral video sequences. We propose to decompose the integral video sequence down to viewpoint video sequences and jointly exploit motion and disparity redundancies to maximize the compression. We further propose an optimization technique based on evolutionary strategies to minimize the computational complexity of the joint motion disparity estimation. Experimental results demonstrate that Joint Motion and Disparity Estimation can achieve over 1 dB objective quality gain over normal motion estimation. Once combined with Evolutionary strategy, this can achieve up to 94% computational cost saving. © 2007 IEEE.

This paper is synopsis of a recently proposed solution for treating patients who suffer from Phantom Limb Pain (PLP). The underpinning approach of this research and development project is based on an extension of "mirror box" therapy which has had some promising results in pain reduction. An outline of an immersive individually tailored environment giving the patient a virtually realised limb presence, as a means to pain reduction is provided. The virtual 3D holographic environment is meant to produce immersive, engaging and creative environments and tasks to encourage and maintain patients' interest, an important aspect in two of the more challenging populations under consideration (over-60s and war veterans). The system is hoped to reduce PLP by more than 3 points on an 11 point Visual Analog Scale (VAS), when a score less than 3 could be attributed to distraction alone. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.

The objectives of this paper is to present a novel adaptive edge extraction algorithm, based on processing of the local histograms of small non-overlapping blocks of the output of the first derivative of a narrow 2D Gaussian filter. It is shown that the proposed edge extraction algorithm provides the best trade off between noise rejection and accurate edge localisation and resolution. The proposed edge detection algorithm starts by convolving the image with a narrow 2D Gaussian smoothing filter to minimise the edge displacement, and increase the resolution and detectability. Processing of the local histogram of small non-overlapping blocks of the edge map is carried out to perform an additional noise rejection operation and automatically determine the local thresholds. © 2006 IEEE.

Integral imaging is a technique capable of displaying 3-D images with continuous parallax in full natural color. It is one of the most promising methods for producing smooth 3-D images. Extracting depth information from integral image has various applications ranging from remote inspection, robotic vision, medical imaging, virtual reality, to content-based image coding and manipulation for integral imaging based 3-D TV. This paper presents a method of generating a depth map from unidirectional integral images through viewpoint image extraction and using a hybrid disparity analysis algorithm combining multi-baseline, neighborhood constraint and relaxation strategies. It is shown that a depth map having few areas of uncertainty can be obtained from both computer and photographically generated integral images using this approach. The acceptable depth maps can be achieved from photographic captured integral images containing complicated object scene. © 2007 IEEE.

An automatic edge thresholding approach, based on investigation of local histograms of small nonoverlapping blocks of the quantised edge magnitude, is proposed. The edge magnitude is first quantised then divided into small nonoverlapping blocks. A threshold for each block is chosen using an iterative procedure. In this paper the effect of the choice of the quantiser is investigated using a quantitative measure. The performance of three quantisers is studied and compared to the results obtained without quantisation of the gradient image and to previously reported method for automatic threshold selection for edge detection.

Integral imaging is employed as part of a three-dimensional imaging system, allowing the display of full colour images with continuous parallax within a wide viewing zone. A significant quantity of data is required to represent a captured integral 3D image with high resolution. In this paper, a novel approach to the problem of compressing the significant quantity of data required to represent integral 3D video is presented. The algorithm is based on 3D discrete cosine transform (3D-DCT). It takes advantage of the high cross-correlation between the sub-images generated by the microlens array and it takes advantage of the viewpoints image representation of unidirectional image to decrease the number of bits required to code the motion vectors. The algorithm has been simulated on several generated integral 3D videos.

Computer generation of 3D holoscopic imaging requires higher resolution display than normal computer images in order to produce 3D images with acceptable quality. The efficiency of the shadow cache increases as the resolution of the image increases. In order to apply shadow cache to ray tracing of 3D holoscopic images, coherent grouping of pixels that ensures successively tracing of pixels whose primary rays share spatial coherence, is required. That increases the number shadow rays that utilise the shadow cache and save large number of intersection tests. In this paper, the optimum pixel grouping for improving the coherence and the shadow cache in the computer generation of 3D holoscopic content is investigated. Experimental results show, that up to a 13.7% improvement in execution time can be achieved by proper pixel grouping. © 2010 IEEE.

In this paper, we report the theoretical and experimental implementation of a photonic mixer for Radio-Over-Fiber (RoF) transmission systems, which incorporates an all-optical 10.87 GHz microwave frequency signal generator based on beating laser frequency with its first order Stimulated Brillouin Scattering (SBS) frequency shift. A 13GHz Radio Frequency (RF) is down-converted to 2.13 GHz Intermediate Frequency (IF) signal. The proposed system configuration represents a cost-effective photonic mixer that can be deployed for up and down conversion around 11 GHz in RoF transmission systems. The optically generated microwave signal of 10.87 GHz has a phase noise of -109 dBc/Hz at 15-MHz offset. The proposed photonic mixer exhibits a Spurious-Free Dynamic Range (SFDR) of 93dB.Hz

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The aim of this paper is to provide an overview of the 3D Holoscopic imaging technology which is used employed as part of a three-dimensional imaging system, allowing the display of full colour images with continuous parallax within a wide viewing zone.

Two new high-performance bidirectional mixed radix-2

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A new cell architecture for high performance digit-serial computation is presented. The design of this cell is based on the feedforward of the carry digit, which allows a high level of pipelining to increase the throughput rate. This will give designers greater flexibility in finding the best tradeoff between hardware cost and throughput rate. The effect of the number of pipelining levels on the throughput rate and hardware cost are presented. © 1993, The Institution of Electrical Engineers. All rights reserved.

An error analysis of the 2-D FIR digital Alters realisation using DPCM video signal processing is outlined. Quantisation errors due to coding and finite word length are studied. Simulation results demonstrating the coherence between the theoretical and the experimental results are presented. The main conclusion that can be drawn from the theoretical and empirical results is that there is a minimum value of the filter coefficients’ word length after which no improvement in the signal-to-noise ratio (SNR) is possible. However, subjective tests have shown that images obtained using the DPCM realisation with this minimum word length have similar visual quality as that obtained using conventional filters with infinite precision. © 1991 The Institution of Electrical Engineers. All rights reserved.

A new regular implementation of a diminished-1 multiplier is presented which requires less silicon area and achieves higher speed than existing designs. For a multiplier where the modulus involved is a 34% increase in the speed of operation is achieved in comparison to that of Sunder et al. © 1994, IEE. All rights reserved.

A novel automatic edge extraction algorithm, based on investigation of local histograms of small non-overlapping blocks of the output of the first derivative of a narrow 2D Gaussian filter, is presented. It is shown that the proposed algorithm provides the best trade-off between noise suppression and correct edge localisation.

A new two's complement parallel multiplier architecture is proposed. It is based on the partitioning of one of the operands into four groups. Array multipliers without the final adder are used to produce eight partial product terms. This allows more efficient use of 4:2-compressors in the intermediate stages. It is shown that the proposed multiplier has better performance than existing designs with respect to both area and speed.

The subject of the future of the interactive Television medium has become a topic of great interest to the academic and industrial communities particularly since in the recent years there has been a dramatic increase in the pace of innovation of convergence of digital TV systems and services. The purpose of this paper is to provide a brief overview of what we know as digital TV converged services, to present and categorise the digital Television middleware technologies that contributed to it, and to present possible future trends and directions. A new Television era of converged wireless and mobile content delivery, user-authored content, multimodal interaction, intelligent personalisation, smart space awareness, and 3D content sensations is foreseen, creating ambient and immersive experiences.

Integral imaging is a technique capable of displaying 3D images with continuous parallax in full natural color. It has been reported by many research groups and is becoming a viable alternative for 3D television. With the development of 3D integral imaging, image compression becomes mandatory for the storage and transmission of 3D integral images. In this paper, the use of the lifting scheme in the application of a 3D Wavelet Transform for the compression of 3D Integral Images is proposed. The method requires the extraction of different viewpoint images from an integral image. The 3D wavelet decomposition is computed by applying three separate 1D transforms along the coordinate axes of the given sequence of Viewpoint Images. The spatial wavelet decompositions on a single viewpoint and on the inter-viewpoint images are performed using the biorthogonal Cohen-Debauchies-Feauveau 9/7 and 5/3 filter banks, respectively. All the resulting wavelet coefficients from application of the 3D wavelet decomposition are arithmetic encoded. Simulations are performed on a set of different grey level 3D Integral Images using a uniform scalar quantizer with deadzone. The results for the average of the four intensity distributions are presented and compared with previous use of 2D DWT and 3D-DCT based schemes. It was found that the algorithm achieves better rate-distortion performance and reconstructs the images with much better image quality at very low bit rates. © 2011 IEEE.

A novel approach to increase the speed and reduce the hardware requirement of 2-D systolic convolvers for real-time video signal/image processing is proposed. This is achieved by coding video signals/images more efficiently using six-bit 1-D DPCM coding. It is shown that using six-bit differential pulse-code modulation processing results in a 57% improvement in speed and a significant saving in the cost of 2-D systolic convolvers. The effect of quantisation errors on DPCM image convolution is also presented. © 1990, The Institution of Electrical Engineers. All rights reserved.

The Standard Plenoptic Camera (SPC) is an innovation in photography, allowing for acquiring two-dimensional images focused at different depths, from a single exposure. Contrary to conventional cameras, the SPC consists of a micro lens array and a main lens projecting virtual lenses into object space. For the first time, the present research provides an approach to estimate the distance and depth of refocused images extracted from captures obtained by an SPC. Furthermore, estimates for the position and baseline of virtual lenses which correspond to an equivalent camera array are derived. On the basis of paraxial approximation, a ray tracing model employing linear equations has been developed and implemented using Matlab. The optics simulation tool Zemax is utilized for validation purposes. By designing a realistic SPC, experiments demonstrate that a predicted image refocusing distance at 3.5 m deviates by less than 11% from the simulation in Zemax, whereas baseline estimations indicate no significant difference. Applying the proposed methodology will enable an alternative to the traditional depth map acquisition by disparity analysis.

The rapid momentum of the technology progress in the recent years has led to a tremendous rise in the use of biometric authentication systems. The objective of this research is to investigate the problem of identifying a speaker from its voice regardless of the content. In this study, the authors designed and implemented a novel text‐independent multimodal speaker identification system based on wavelet analysis and neural networks. Wavelet analysis comprises discrete wavelet transform, wavelet packet transform, wavelet sub‐band coding and Mel‐frequency cepstral coefficients (MFCCs). The learning module comprises general regressive, probabilistic and radial basis function neural networks, forming decisions through a majority voting scheme. The system was found to be competitive and it improved the identification rate by 15% as compared with the classical MFCC. In addition, it reduced the identification time by 40% as compared with the back‐propagation neural network, Gaussian mixture model and principal component analysis. Performance tests conducted using the GRID database corpora have shown that this approach has faster identification time and greater accuracy compared with traditional approaches, and it is applicable to real‐time, text‐independent speaker identification systems.

Recent developments in computational photography enabled variation of the optical focus of a plenoptic camera after image exposure, also known as refocusing. Existing ray models in the field simplify the camera's complexity for the purpose of image and depth map enhancement, but fail to satisfyingly predict the distance to which a photograph is refocused. By treating a pair of light rays as a system of linear functions, it will be shown in this paper that its solution yields an intersection indicating the distance to a refocused object plane. Experimental work is conducted with different lenses and focus settings while comparing distance estimates with a stack of refocused photographs for which a blur metric has been devised. Quantitative assessments over a 24 m distance range suggest that predictions deviate by less than 0.35 % in comparison to an optical design software. The proposed refocusing estimator assists in predicting object distances just as in the prototyping stage of plenoptic cameras and will be an essential feature in applications demanding high precision in synthetic focus or where depth map recovery is done by analyzing a stack of refocused photographs.

In this paper, we demonstrate light field triangulation to determine depth distances and baselines in a plenoptic camera. Advances in micro lenses and image sensors have enabled plenoptic cameras to capture a scene from different viewpoints with sufficient spatial resolution. While object distances can be inferred from disparities in a stereo viewpoint pair using triangulation, this concept remains ambiguous when applied in the case of plenoptic cameras. We present a geometrical light field model allowing the triangulation to be applied to a plenoptic camera in order to predict object distances or specify baselines as desired. It is shown that distance estimates from our novel method match those of real objects placed in front of the camera. Additional benchmark tests with an optical design software further validate the model’s accuracy with deviations of less than ±0.33% for several main lens types and focus settings. A variety of applications in the automotive and robotics field can benefit from this estimation model.

Plenoptic cameras are receiving increased attention in scientific and commercial applications because they capture the entire structure of light in a scene, enabling optical transforms (such as focusing) to be applied computationally after the fact, rather than once and for all at the time a picture is taken. In many settings, real-time interactive performance is also desired, which in turn requires significant computational power due to the large amount of data required to represent a plenoptic image. Although GPUs have been shown to provide acceptable performance for real-time plenoptic rendering, their cost and power requirements make them prohibitive for embedded uses (such as in-camera). On the other hand, the computation to accomplish plenoptic rendering is well structured, suggesting the use of specialized hardware. Accordingly, this paper presents an array of switch-driven finite impulse response filters, implemented with field programmable gate array (FPGA) to accomplish high-throughput spatial-domain rendering. The proposed architecture provides a power-efficient rendering hardware design suitable for full-video applications as required in broadcasting or cinematography. A benchmark assessment of the proposed hardware implementation shows that real-time performance can readily be achieved, with a one order of magnitude performance improvement over a GPU implementation and three orders of magnitude performance improvement over a general-purpose CPU implementation.

The expansion of 3D technology will enable observers to perceive 3D without any eye-wear devices. Holoscopic 3D imaging technology offers natural 3D visualisation of real 3D scenes that can be viewed by multiple viewers independently of their position. However, the creation of a super depth-map and reconstruction of the 3D object from a holoscopic 3D image is still in its infancy. The aim of this work is to build a high-quality depth map of a real 3D scene from a holoscopic 3D image through extraction of multi-view high resolution Viewpoint Images (VPIs) to compensate for the poor features of VPIs. To manage this, we propose a reconstruction method based on the perspective formula to convert sets of directional orthographic low resolution VPIs into perspective projection geometry. Following that, we implement an Auto-Feature point algorithm for synthesizing VPIs to distinctive Feature-Edge (FE) blocks to localize and provide an individual feature detector that is responsible for integration of 3D information. Detailed experiments proved the reliability and efficiency of the proposed method, which outperforms state-of-the-art methods for depth map creation. © 2014 IEEE.

Existing imaging modalities of urologic pathology are limited by three-dimensional (3D) representation on a two-dimensional screen. We present 3D-holoscopic imaging as a novel method of representing Digital Imaging and Communications in Medicine data images taken from CT and MRI to produce 3D-holographic representations of anatomy without special eyewear in natural light. 3D-holoscopic technology produces images that are true optical models. This technology is based on physical principles with duplication of light fields. The 3D content is captured in real time with the content viewed by multiple viewers independently of their position, without 3D eyewear. We display 3D-holoscopic anatomy relevant to minimally invasive urologic surgery without the need for 3D eyewear. The results have demonstrated that medical 3D-holoscopic content can be displayed on commercially available multiview auto-stereoscopic display. The next step is validation studies comparing 3D-Holoscopic imaging with conventional imaging.

An integral imaging system is employed as part of a three dimensional imaging system, allowing display of full color images with continuous parallax within a wide viewing zone. A novel approach to the problem of compressing the significant quantity of data required to represent integral 3D video is presented and it is shown that the reduction in bit cost achieved makes possible transmission via conventional broadcast channels. ©2005 Copyright SPIE - The International Society for Optical Engineering.

3D Holoscopic Imaging (3DHI) is a promising technique for viewing natural continuous parallax 3D objects within a wide viewing zone using the principle of 'Fly's eye'. The 3D content is captured using a single aperture camera in real-time and represents a true volume spatial optical model of the object scene. The 3D content viewed by multiple viewers independently of their position, without 3D eyewear glasses. The 3DHI technique merely requires a single recording that the acquisition of the 3D information and the compactness of depth measurement that is used has been attracting attention as a novel depth extraction technique. This paper presents a new corresponding and matching technique based on a novel automatic Feature-Match Selection (FMS) algorithm. The aim of this algorithm is to estimate and extract an accurate full parallax 3D model form from a 3D Omni-directional Holoscopic Imaging (3DOHI) system. The basis for the novelty of the paper is on two contributions: feature blocks selection and corresponding automatic optimization process. There are solutions for three main problems related to the depth map estimation from 3DHI: uncertainty and region homogeneity at image location, dissimilar displacements within the matching block around object borders, and computational complexity. © 2013 IEEE.

In this paper a single aperture motion picture camera based on holoscopic imaging used to generate high-resolution stereoscopic image. The idea of single aperture camera reduces the very cumbersome and expensive of dual cameras in stereoscopic production. The camera is known as light field camera, which was first proposed in 1908 by lippmann [1]. The rendering method relied on upsampling, shift and integrating of different views to extract stereo images. This is the first experiment attempted to generate stereo form holoscopic content on motion capturing, where researchers so far have been experimenting on still images. In this paper presents motion picture image rendering on holoscopic content to generate content for stereoscopic systems. We have carried out experiments with focused ploneptic camera on a single stage omnidirectional integral camera arrangement with capturing both horizontal and vertical parallax, using a low cost lens array and relay lens. Our results show an improvement in the resolution of images with artifact free and also the rendered stereo content are played back on polarized stereoscopic system and anaglyph system to perceive the 3D depth using filter glasses in our experimental section. © 2013 IEEE.

Holoscopic 3D imaging also known as Integral imaging is an attractive technique for creating full color 3D optical models that exist in space independently of the viewer. The constructed 3D scene exhibits continuous parallax throughout the viewing zone. In order to achieve depth control, robust and real-time, a single aperture holoscopic 3D imaging camera is used for recording holoscopic 3D image using a regularly spaced array of microlens arrays, which view the scene at a slightly different angle to its neighbor. However, the main problem is that the microlens array introduces a dark borders in the recorded image and this causes errors at playback on the holoscopic 3D Display. This paper proposes a reference based pre-processing of holoscopic 3D image for autostereoscopic holoscopic 3D displays. The proposed method takes advantages of microlens as reference point to detect amount of introduced dark borders and reduce/remove them from the holoscopic 3D image. © 2013 IEEE.

Autostereoscopic 3D Display is robustly developed and available in the market for both home and professional users. However 3D resolution with acceptable 3D image quality remains a great challenge. This paper proposes a novel pixel mapping method for refining dark areas between two pinholes by distributing it into 3 times smaller dark areas and creating micro-pinholes in parallax barriers based holoscopic 3D displays. The proposed method allows to project RED, GREEN, BLUE subpixels separately from 3 different pinholes and it distributes the dark spaces into 3 times smaller dark spaces, which become unnoticeable and improves quality of the constructed holoscopic 3D scene significantly. Parallax barrier technology refers to a pinhole sheet or device placed in front or back of a liquid crystal display, allowing to project viewpoint pixels into space that reconstructs a holoscopic 3D scene in space. The holoscopic technology mimics the imaging system of insects, such as the fly, utilizing a single camera, equipped with a large number of micro-lenses or pinholes, to capture a scene, offering rich parallax information and enhanced 3D feeling without the need of wearing specific eyewear. © 2013 IEEE.

Integral Imaging (InIm) is one of the most promising technologies for producing full color 3-D images with full parallax. InIm requires only one recording in obtaining 3D information and therefore no calibration is necessary to acquire depth values. The compactness of using InIm in depth measurement has been attracting attention as a novel depth extraction technique. In this paper, an algorithm for depth extraction that builds on previous work by the authors is presented. Three main problems in depth map estimation from InIm have been solved; i) the uncertainty and region homogeneity at image location where errors commonly appear in disparity process, ii) dissimilar displacements within the matching block around object borders, iii) object segmentation. This method is based on the distribution of the sample variance in sub-dividing non-overlapping blocks. A descriptor which is unique and distinctive for each feature on InIm has been achieved. Comparing to state-of-the-art techniques, it is shown that the proposed algorithm has improvements on two aspects: 1) depth map extraction level, 2) computational complexity. © 2013 IEEE.

The Autostereoscopic Multiview 3D Display is robustly developed and widely adopted by both home and professional users however Multiview 3D content generation remains a great challenge. This paper proposes a novel method for Multiview 3D content generation and it describes the necessary steps for Holoscopic 3D image rendering for autostereoscopic Multiview 3D display. The Holoscopic imaging technology mimics the imaging system of insects, such as the fly, utilizing a single camera, equipped with a large number of micro-lenses, to capture a scene, offering rich parallax information and enhanced 3D feeling without the need of wearing specific eyewear. In addition a 3D pixel mapping/conversion algorithm has been developed that is supported by the Multiview 3D display. © 2013 IEEE.

This paper proposes a novel mean adaptive 3DDCT algorithm for 3D content to achieve the optimal result by trading of quality and compression of 3D image. The proposed method enables users to adjust the compression rate according to application areas by applying small blocks to the more detailing area (non -stationary regions) and larger blocks to the background or less details area (homogenous regions) [1]. This proposed method 'Mean Adaptive 3D-DCT' is applied on Holoscopic 3D images also known as Integral Images. In addition, the experiment results prove the method is applicable to any 3D content. © 2013 IEEE.

This paper presents new algorithm for improving the visual definition quality of real integral images computationally throughimage reconstructing. The proposed algorithm takes advantage of true 3D 'Integral imaging'. A real world scene is recorded based on the fly's eye technique, which is simulated by an array of microlensesn The proposed method works on orthographic viewpoint images, where shift-and-integration of the neighboring viewpoints are used with quadratic interpolation to increase the visual quality on the final image. This process returns a standard photographic image with enhanced image quality. Detailed experiments have been conducted to demonstrate the effectiveness of proposed method and results are offered. © 2013 IEEE.

This paper presents a wavelet-based lossy compression technique for unidirectional 3D integral images (U1I). The method requires the extraction of different viewpoint images from the integral image. A single viewpoint image is constructed by extracting one. pixel from each microlens, then each viewpoint image is decomposed using a Two Dimensional Discrete Wavelet Transform (2D-DWT). The resulting array of coefficients contains several frequency bands. The lower frequency bands of the viewpoint images are assembled and compressed using a 3 Dimensional Discrete Cosine Transform (3D-DCT) followed by Huffman coding. This will achieve decorrelation within and between 2D low frequency bands from the different viewpoint images. The remaining higher frequency bands are Arithmetic coded. After decoding and decompression of the viewpoint images using an inverse 3D-DCT and an inverse 2D-DWT, each pixel from every reconstructed viewpoint image is put back into its original position within the microlens to reconstruct the whole 3D integral image. Simulations were performed on a set of four different grey level 3D UII using a uniform scalar quantizer with deadzone. The results for the average of the four UII intensity distributions are presented and compared with previous use of 3D-DCT scheme. It was found that the algorithm achieves better rate-distortion performance, with respect to compression ratio and image quality at very low bit rates.

A programmable systolic array used for real time video signal processing is introduced. The processor is more than twice as fast and requires less hardware than multiplier-based processors. This is achieved by processing video signals that are coded more efficiently using differential pulse code modulation (DPCM). Tests carried out on the implementation of quadrature mirror filters (QMFs) indicate that images obtained using DPCM processing will have the same visual quality as those obtained using conventional processing.

A novel and low-cost embedded hardware architecture for real-time refocusing based on a standard plenoptic camera is presented in this study. The proposed layout design synthesizes refocusing slices directly from micro images by omitting the process for the commonly used sub-aperture extraction. Therefore, intellectual property cores, containing switch controlled Finite Impulse Response (FIR) filters, are developed and applied to the Field Programmable Gate Array (FPGA) XC6SLX45 from Xilinx. Enabling the hardware design to work economically, the FIR filters are composed of stored product as well as upsampling and interpolation techniques in order to achieve an ideal relation between image resolution, delay time, power consumption and the demand of logic gates. The video output is transmitted via High-Definition Multimedia Interface (HDMI) with a resolution of 720p at a frame rate of 60 fps conforming to the HD ready standard. Examples of the synthesized refocusing slices are presented. © 2014 SPIE-IS and T.

A new architecture for high performance digit-serial vector inner product (VIP) which can be pipelined to the bit-level is introduced. The design of the digit-serial vector inner product is based on a new systematic design methodology using radix-2

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Recently, 3D display technology, and content preparation and creation tools have been under vigorous development. Consequently, they are also widely adopted by home and professional users. 3D digital repositories are increasing and becoming available ubiquitously. However, there is not yet a single 3D content search and retrieval platform. In this paper, we propose and present the development of a novel approach for 3D content search and retrieval which is called Dynamic hyperlinker for 3D content search and retrieval. It advances 3D multimedia navigability and searchability by creating dynamic links for selectable and clickable objects in the scene while the 3D video clip is being replayed. The proposed system involves 3D video processing, such as detecting/tracking clickable objects, annotating objects, and metadata engineering. Such system attracts the attention from both home and professional users such as broadcasters and digital content providers. The experiment is conducted on Holoscopic 3D images 'also known as integral images'. © 2013 IEEE.

An algorithm for image compression, based on local histogram analysis, is presented. A given image is compressed by dividing the image into nonoverlapping square blocks and coding the edge information in each block. The edge information is extracted by first differentiating the original image, quantizing the differential image, then investigated the local histogram of small blocks of the differential image. Depending on the behavior of the local histograms in the differential image, the corresponding blocks in the original image are classified into visually active and visually continuous blocks. The visually continuous blocks are coded using the mean value only. A visually active block is coded using the location and orientation of the edge within the block. As a result, the compression ratio of the proposed algorithm depends on the behavior of the local histogram, which in turn depends heavily on the quantization process of the differential image. In this paper, the effect of the quantization of the differential image on the compression ratio and the image quality is discussed.

The objectives of this paper is to present a novel multi-resolution edge extraction algorithm, based on processing of the local histograms of small non-overlapping blocks of the output of the first derivative of a narrow 2D Gaussian filter. The proposed edge detection algorithm starts by convolving the image with a narrow 2D Gaussian smoothing filter to minimise the edge displacement, and increase the resolution and detectability. Processing of the local histogram of small non-overlapping blocks of the edge map is carried out to perform an additional noise rejection operation and automatically determine the local thresholds. It is shown that the proposed edge extraction algorithm provides the best trade off between noise rejection and accurate edge localisation and resolution. ©2007 IEEE.

A new parallel multiplier design is proposed based on the technique of partitioning the operands into four groups however using different grouping and a combination of 4:2 compressor carry save adders for the accumulation of the 16 partial product terms. Also a design methodology of parallel multipliers is proposed which gives the designer more fexibility in finding the best trade off between the throughput rate and the hardware cost.

In this paper, a novel approach is proposed for selecting the thresholds of edge strength maps from its local histogram. This threshold selection technique is based on finding the threshold for small blocks of the edge map. For each block the threshold is chosen using an iterative procedure. The effect of the choice of the size of the block will be discussed. In this paper, the edge strength map is quantised to reduce the computation of the iterative threshold selection algorithm as well as the memory requirement. It will be shown that the quantisation of the edge map improves the performance of the local iterative threshold selection algorithm. Typical examples of the tests carried out will be presented.

A new serial-serial multiplier is being proposed which requires only N/2 conventional cells for multiplying two N-bit numbers, compared to N cells needed in existing structures. The significant aspect of the new design is that this 50% reduction in hardware has been achieved without degrading the speed performance. This is achieved by exploiting the fact that some cells are idle for most of the multiplication operation. In the new design, the computations of these cells are re-mapped to other cells, which makes them redundant. The proposed architecture is the first bit serial-serial structure with a comparable area-time performance to the bit serial-parallel structures. Furthermore the proposed structure is superior in Area-Time performance to all existing serial-serial realizations.

A mathematical model for a three-dimensional omnidirectional integral recording camera system that uses either circular- or hexagonal-based spherical surface microlens arrays is derived. The geometry of the image formation and recording process is fully described. Matlab is then used to establish the number of recorded micro-intensity distributions representing a single object point and their dependence on spatial position. The point-spread function for the entire optical process for both close and remote imaging is obtained, and the influence of depth on the point-spread dimensions for each type of microlens and imaging condition is discussed. Comparisons of the two arrangements are made, based on the illustrative numerical results presented. © 2001 Optical Society of America.

Integral imaging is employed as part of a three-dimensional imaging system, allowing the display of full colour images with continuous parallax within a wide viewing zone. A significant quantity of data is required to represent a captured integral 3D image with high resolution. A lossy compression scheme has been developed based on the use of a 3D-DCT, which make possible efficient storage and transmission of such images, while maintaining all information necessary to produce a high quality 3D display. In this paper, a novel approach to the problem of compressing the significant quantity of data required to represent integral 3D images is presented. The algorithm is based on using a variable number of microlens images (or sub-images) in the computation of the 3D-DCT. It involves segmentation of the planar mean image formed by the mean values of the microlens images and it takes advantage of the high cross-correlation between the sub-images generated by the microlens array. The algorithm has been simulated on several integral 3D images. It was found that the proposed algorithm improves the rate-distortion performance when compared to baseline JPEG and previously reported 3D-DCT compression scheme with respect to compression ratio and subjective and objective image quality. © 2002 Elsevier Science B.V. All rights reserved.

An approach to the realization of 2D FIR fillers based on a novel radix-differential arithmetic is introduced. The differential algorithm is accomplished by coding the input video signal more efficiently using a DPCM coding system. Whereas the filter's coefficients are fed in digit serial fashion and specified using radix-2

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The V-RaAP software (written in C++) enables the implementation of Radix Array Processors, expressed as iterative equations, into Field Programmable Gate Arrays (FPGA’s). The V-RaAP software is not a compiler which translates C++ into VHDL, Rather, the V-RaAP C++ program is a high-level explicit description of structural VHDL that implements a RaAP algorithm in a hierarchical manner. When the C++ program is executed it automatically generates a number of VHDL flies containing the entity and architecture specifications of the components which make up the final design. The code generated is equivalent to a hand crafted VHDL design. This is made possible because the RaAP iterative algorithm contains all the information specifying the functionality and interconnects of the architectures.

This paper presents for the first time, a theory for obtaining the optimum pixel grouping for improving the coherence and the shadow cache in integral 3D ray-tracing in order to reduce execution time. A theoretical study of the number of shadow cache hits with respect to the properties of the lenses and the shadow size and its location is discussed with analysis for three different styles of pixel grouping in order to obtain the optimum grouping. The first style traces rows of pixels in the horizontal direction, the second traces similar pixels in adjacent lenses in the horizontal direction, and the third traces columns of pixels in the vertical direction. The optimum grouping is a combination of all three dependant up on the number of cache hits in each. Experimental results show validation of the theory and tests on benchmark scenes show that up to a 37% improvement in execution time can be achieved by proper pixel grouping. © 2002 SPIE · 0277-786X/02/$15.00.

A VLSI architecture for three-dimensional discrete cosine transform (3D DCT) is proposed. The 3D DCT is decomposed into 1D DCTs computed in each of the three dimensions. The focus of this paper is in the design of the matrix transpose required prior to the computation of the final 1D DCT which corresponds to the third dimension. In this paper, this matrix transpose is divided into N memory units each performing the row-column transpose and switching networks to allow correct read and write. This architecture uses 3N multiplier-accumulators and N+1 (N×N)-words memory transpose to evaluate an (N×N×N)-point DCT at a rate of one complete 3D transform per N

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A new architecture for digit-serial multiplication is presented. The new digit-serial multiplier is the first reported systolic design where the delay in obtaining the least significant digit (i.e. the initial delay) is independent of the number of digits and hence the wordlength. Although the new architecture has a bidirectional data flow, all the cells are used with 100% efficiency. This is achieved by combining, in a novel way, the operation of two basic cells used in the conventional structures. The proposed multiplier is the ideal design to use in DSP structures that have data feedback paths such as IIR filters, because it has localised communications and has the lowest possible latency as well as being modular and regular. The new structure also allows a high level of pipelining to increase the throughput rate. The performance and the effect of pipelining levels on the throughput rate and hardware cost for the new structure is also presented to allow designers to find the best tradeoff between hardware cost and multiplication time. © IEE, 1996.

A numerical analysis of a novel birefringent photonic crystal fiber (PCF) biosensor constructed on the surface plasmon resonance (SPR) model is presented in this paper. This biosensor configuration utilizes circular air holes to introduce birefringence into the structure. This PCF biosensor model shows promise in the area of multiple detection using HE11

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In this paper, new architectures for fast and efficient conversions from the weighted binary numbers to their 3-moduli (2

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Holoscopic 3D imaging also known as Integral imaging is a promising technique for creating full color 3D optical models that exist in space independently of the viewer. The images exhibit continuous parallax throughout the viewing zone. In order to achieve depth control, robust and real-time, a single aperture holoscopic 3D imaging camera is used for recording holoscopic 3D image using a regularly spaced array of small lenslets, which view the scene at a slightly different angle to its neighbor. However, the main problem the holoscopic 3D camera aperture faces is that it is not big enough for recording larger scene with existing 2D camera sensors. This paper proposes a novel reference based holoscopic 3D camera aperture stitching method that enlarges overall viewing angle of the holoscopic 3D camera in post-production after the capture. © 2014 IEEE.

Plenoptic cameras have been used to computationally generate viewpoint images from the captured light field. This paper aims to provide a prediction of corresponding virtual camera positions based on the parameters of a standard plenoptic camera setup. Furthermore, by tracing light rays from the sensor to the object space, a solution is proposed to estimate the baseline of viewpoints. By considering geometrical optics, the suggested approach has been implemented in Matlab and assessed using Zemax, a real ray tracing simulation tool. Thereby, the impact of different main lens locations is investigated. Results of the baseline approximation indicate that estimates obtained by the proposed model deviate by less than 0.2% compared to the complex real ray tracing method. © 2014 IEEE.

An algorithm to improve block truncation coding for image compression is proposed. Images to be compressed are first differentiated and edge information is extracted by investigation of the histogram of small nonoverlapping blocks of the differential image. The image is classified into visually active and visually continuous blocks which are then coded individually.

The objectives of this paper is to present a novel edge extraction algorithm, based on differentiation of the local histograms of small non-overlapping blocks of the output of the first derivative of a narrow 2D Gaussian filter. It is shown that the proposed edge extraction algorithm provides the best trade off between noise rejection and accurate edge localisation and resolution. The proposed edge detection algorithm starts by convolving the image with a narrow 2D Gaussian smoothing filter to minimise the edge displacement, and increase the resolution and detectability. Processing of the local histogram of small non-overlapping blocks of the edge map is carried out to perform an additional noise rejection operation and automatically determine the local thresholds. The results obtained with the proposed edge detector are compared to the Canny edge detector.

This paper seeks to explore a method to accurately correct geometric distortions caused during the capture of three-dimensional (3-D) integral images. Such distortions are rotational and scaling errors which, if not corrected, will cause banding and moire effects on the replayed image. The method for calculating the angle of deviation in the 3-D Integral Images is based on Hough Transform. It allows detection of the angle necessary for correction of the rotational error. Experiments have been conducted on a number of 3-D integral image samples and it has been found that the proposed method produces results with accuracy of 0.05 deg. © 2006 IEEE.

In this paper we propose an efficient approach to use an adaptable ES algorithm to compress motion information of 3D integral video sequences. The integral video sequence is decomposed into 8 viewpoint video sequences and a block search is performed to exploit the motion estimation redundancies between neighboring blocks to maximize the compression. An Adaptable Evolutionary Strategy (ES) based search algorithm is used to reduce the coding complexity. Experimental results show that the ES based strategy can reduce the motion estimation complexity by 90%. ©2007 IEEE.

The aim of the paper is to provide an insight of the progress made in 3D Holoscopic video technology. The paper will show an example of a coding technique based on 3D discrete cosine transform (DCT) which take full advantage of the data structure of 3D Holoscopic video. Various grouping of micro-images in a single 3D DCT computation is discussed.

The objective of this paper is to develop a sufficiently flexible network flow model that can be used to investigate the effect of hourly traffic flows on the future fixed and wireless IP networks as a result of introducing a range of different classes of 3D applications into an existing mix of heterogeneous services.

A new parallel architecture for the computation of a vector inner product is presented. The design is based on an extension of the radix-2

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In this paper we propose a novel approach to use both motion and disparity information to compress 3D integral video sequences. The integral video sequence is decomposed into 8 viewpoint video sequences and a block search is performed to jointly exploit the motion and disparity redundancies to maximize the compression. A half pixel refinement algorithm is then applied by interpolating macro blocks in the previous frame to further improve the video quality. Experimental results show that the method proposed achieves approximately a 1.5dB gain in video quality over a full search motion algorithm. © 2007 IEEE.

In recent years there has been a considerable amount of development work been made in the area of Three-Dimensional (3D) imaging systems and displays. Such systems have attracted the attention and have been widely consumed by both home and professional users in sectors such as entertainment and medicine. However, computer generated 3D content remains a challenge as the 3D scene construction requires contributions from thousands of micro images 'also known as elemental images'. Rendering microlens images is very time-consuming because each microlens image is rendered by a perspective or orthographic pinhole camera in a computer generated environment. In this paper we propose and present the development of a new method to simplify and speed-up the rendering process in computer graphics. We also describe omnidirectional 3D image recoding using a two-layer orthographic camera. Results show that it's rendering performance makes it an ideal candidate for real-time/interactive 3D content visualization application(s). © 2013 IEEE.

The development of 3D TV systems and displays for public use require that several important criteria be satisfied. The criteria are that the perceived resolution is as good as existing 2D TV, the image must be in full natural colour, compatibility with current 2D systems in terms of frame rate and transmission data must be ensured, human-factors concerns must be satisfied and seamless autostereoscopic viewing provided. There are several candidate 3D technologies, for example stereoscopic multiview, holographic and integral imaging that endeavor to satisfy the technological and other conditions. The perceived advantages of integral imaging are that the 3D data can be captured by a single aperture camera, the display is a scaled 3D optical model, and in viewing accommodation and convergence are as in normal sighting (natural) thereby preventing possible eye strain. Consequently it appears to be ideal for prolonged human use. The technological factors that inhibited the possible use of integral imaging for TV display have been shown to be less intractable than at first thought. For example compression algorithms are available such that terrestrial bandwidth is perfectly suitable for transmission purposes. Real-time computer generation of integral images is feasible and the high-resolution LCD panels currently available are sufficient to enable high contrast and high quality image display.

A 3D imaging system utilizes 3D holoscopic imaging to display full-color images with continuous parallax within a wide viewing zone. © 1994-2012 IEEE.

The Imaging Technologies group at De Montfort University has developed an integral 3D imaging system, which is seen as the most likely vehicle for 3D television avoiding psychological effects. To create real fascinating three-dimensional television programs, a virtual studio that performs the task of generating editing and integration the 3D contents involving virtual and real scenes is required. The paper presents, for the first time, the procedures, factors and methods of integrating computer-generated virtual scenes with real objects captured using the 3D integral imaging camera system. The method of computer generation of 3D integral images, where the lens array is modelled instead of the physical camera is described. In the model each micro-lens that captures different elemental images of the virtual scene is treated as an extended pinhole camera. An integration process named integrated rendering is illustrated. Detailed discussion and deep investigation are focused on depth extraction from captured integral 3D images. The depth calculation method from the disparity and the multiple baseline method that is used to improve the precision of depth estimation are also presented. The concept of colour SSD and its further improvement in the precision is proposed and verified.

Analyses of facial and audio features have been considered separately in conventional speaker identification systems. Herein, we propose a robust algorithm for text-independent speaker identification based on a decision-level and feature-level fusion of facial and audio features. The suggested approach makes use of Mel-frequency Cepstral Coefficients (MFCCs) for audio signal processing, Viola-Jones Haar cascade algorithm for face detection from video, eigenface features (EFF) and Gaussian Mixture Models (GMMs) for feature-level and decision-level fusion of audio and video. Decision-level fusion is carried out using PCA for face and GMM for audio through AND voting. Feature-level fusion is investigated by combining both MFCC (audio) and PCA (face) features to construct a hybrid GMM for each speaker. Testing on GRID, a multi-speaker audio-visual database, shows that the decision-level fusion of PCA (face) and GMM (audio) achieves 98.2 % accuracy and it is almost 15 % more efficient than feature-level fusion. © 2012 Springer-Verlag.

Foreground detection is an important step in various video content analysis systems such as object tracking, recognition and counting. Due to the limitations of each algorithm based on its merits and demerits, so far, there is no consensus on the most effective method due to varying nature of videos. Accuracy and timely computational processing are the two main constraints. Whilst other methods only detect the approximate motion part(s) of object(s) in a video, this paper presents a novel approach to detect the motion part(s) and associated object(s) to get the whole subject. Our work detects foreground by using a new automatic masking technique. The proposed technique uses a set of morphological operators to separate foreground and background. The proposed algorithm is an extension of previous works [1-3]. A complex video sequence was tested to detect comprehensive foreground regions of moving object(s). © 2012 IEEE.

This paper presents the results of a depth map algorithm applied to the recorded integral images. The novel idea of this paper is the development of automatic masking procedure, which improves the accuracy the depth map by removing the background noise. This is achieved by applying the set of morphological operators to separate the foreground and background. © 2012 IEEE.

A unique integral imaging system is employed as part of a three dimensional television system, allowing display of full colour 3D images with continuous parallax within a wide viewing zone. A significant quantity of data is required to represent captured integral 3D images with adequate resolution. In this paper a lossy compression scheme is described, based on the use of a three dimensional discrete cosine transform (3D-DCT), which makes possible efficient storage and transmission of such images while maintaining all information necessary to produce a high quality 3D display. The results of simulations performed using the 3D-DCT algorithm are presented and it is shown that rate-distortion performance is vastly improved compared with that achieved using baseline JPEG, with captured integral 3D image data.

For computer generated integral images, a transition line can be observed when the viewer shifts parallel to the lens sheet and reaches the edge of current viewing zone during viewing. This is due to the transition from current viewing zone to the next. The images generated using conventional algorithms will suffer from big transition zone, which damages the replaying visual effect and greatly decreases the effective viewing width. This phenomenon is especially apparent for large size images. The conventional computer generation algorithms of integral images use the same boundary configuration as the micro-lenses, which is straightforward and easy to be implemented, but the cause of large transition zone and narrow viewing angle. This paper presents a novel micro-image configuration and algorithm to solve the problem. In the new algorithm, the boundaries of micro-images are not confined by the physical boundaries but normally larger than them. To achieve the maximum effective viewing width, each micro-image is arranged according to the rules decided by several constraints. The considerations in the selection of optimal parameters are discussed, and new definitions related to this issue are given.

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The paper presents a novel algorithm for object space reconstruction from the planar (2D) recorded data set of a 3D-integral image. The integral imaging system is described and the associated point spread function is given. The space data extraction is formulated as an inverse problem, which proves ill-conditioned, and tackled by imposing additional conditions to the sought solution. An adaptive constrained 3D-reconstruction regularization algorithm based on the use of a sigmoid function is presented. A hierarchical multiresolution strategy which employes the adaptive constrained algorithm to obtain highly accurate intensity maps of the object space is described. The depth map of the object space is extracted from the. intensity map using a weighted Durbin-Willshaw algorithm. Finally, illustrative simulation results are given.

Integral imaging is a technique capable of displaying images with continuous parallax in full natural colour. This paper presents a modified multi-baseline method for extracting depth information from unidirectional integral images. The method involves first extracting sub-images from the integral image. A sub-image is constructed by extracting one pixel from each micro-lens rather than a macro-block of pixels corresponding to a micro-lens unit. A new mathematical expression giving the relationship between object depth and the corresponding sub-image pair displacement is derived by geometrically analyzing the three-dimensional image recording process. A correlation-based matching technique is used to find the disparity between two sub-images. In order to improve the disparity analysis, a modified multi-baseline technique where the baseline is defined as the distance between two corresponding pixels in different sub-images is adopted. The effectiveness of this modified multi-baseline technique in removing the mismatching caused by similar patterns in object scenes has been proven by analysis and experiment results. The developed depth extraction method is validated and applied to both photographic and computer generated unidirectional integral images. The depth estimation solution gives a precise description of object thickness with an error of less than 1.0% from the photographic image in the example. © 2002 SPIE · 0277-786X/02/$15.00.

A new realisation of DPCM video signal/image processing is introduced to increase the throughput rate and reduce the hardware cost of the 2D systolic digital filters. This achieved by using a DPCM coding system with a 2D predictor and a 27-level symmetric nonuniform quantiser prior to processing. The advantage of the symmetric nonuniform quantiser is that the size of memory required for multiplication is reduced by a factor of 16 compared to 4 in the existing DPCM implementations. It is shown that the new realisation results in a 64% increase in the throughput rate and a significant reduction in the hardware cost. From the objective and subjective tests carried out, it is shown that the new realisation results in images with visual quality similar to those obtained using conventional processing. Also, the effect of the choice of the 2D predictor is discussed, where it is shown that a 2D predictor with integer coefficients is the most appropriate for DPCM processing.

A fully parallel architecture for the computation of a two-dimensional (2-D) discrete cosine transform (DCT), based on row-column decomposition is presented. It uses the same one-dimensional (1-D) DCT unit for the row and column computations and (N

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We aim to help improve the quality of life of people with visual disabilities through the application of emerging technologies. Our current research investigates the viability of virtual reality (VR) as an aid for persons with visual disabilities. In this article, we explore the potential of VR-assisted reading. We investigate the reading effects of VR equipment on persons with visual disabilities by utilising variations of standardised optometry-informed reading tests conducted across 24 participants. Test results uncovered that, when comparing a worn VR head-mounted display (HMD) to physical unaided tests, results within a HMD scaled better at closer distances, while unaided tests scaled better with further distances. Using the findings collected and requirements elicited from participants, a prototype document reader was developed for reading text within a VR-immersed 3D environment, allowing low-vision users to customise and configure accessibility features for enhanced reading. This software was tested with 11 new participants alongside user evaluations, allowing us to discover how users perceived text best within our 3D virtual environments, and what features and techniques are required to evolve this accessibility tool further. The user test reported an overwhelmingly positive response to our tool as a feasible reading aid, allowing persons who could not engage (or, due to the difficulty, refusing to) in the reading of material to do so. We also register some limitations and areas for improvement, such as a need for non-functional requirements to be improved, and the aesthetics of our design to be improved going forward.

In the past years, the plenoptic camera aroused an increasing interest in the field of computer vision. Its capability of capturing three-dimensional image data is achieved by an array of micro lenses placed in front of a traditional image sensor. The acquired light field data allows for the reconstruction of photographs focused at different depths. Given the plenoptic camera parameters, the metric distance of refocused objects may be retrieved with the aid of geometric ray tracing. Until now there was a lack of experimental results using real image data to prove this conceptual solution. With this paper, the very first experimental work is presented on the basis of a new ray tracing model approach, which considers more accurate micro image centre positions. To evaluate the developed method, the blur metric of objects in a refocused image stack is measured and compared with proposed predictions. The results suggest quite an accurate approximation for distant objects and deviations for objects closer to the camera device.

Systolic architectures for 2D digital filters are presented. The structures are derived directly from the transfer function. The proposed 2-D systolic arrays for 2-D digital filters have several advantages over the existing 2-D arrays, such as modularity and use of nearest neighbour interconnections. These two features make the proposed architecture versatile and more suitable for VLSI implementation.

In this paper we report a unique approach to measuring oxygen saturation levels by utilising the wavelength of the haemoglobin instead of the conventional absorption difference. Two experiments are set up to measure the wavelength of the haemoglobin bound to oxygen at different oxygen saturation levels with the help of a spectrometer. We report a unique low cost and robust wavelength monitoring SpO2 sensor that measures the SpO2 by using the colour of the blood and not the absorption difference of oxyhaemoglobin and deoxyhaemoglobin. With use of a spectrometer, we show that the wavelength of the oxygen-bound haemoglobin has a relation to the oxygen saturation level. The proposed device is designed and experimentally implemented with a colour sensor to measure the SpO2 level of the blood.

Mixed content is a primary feature of current TV program making and consequently real-time computer generated video in autostereoscopic format is important if 3D TV is going to make an impact. In this paper, an approach for computer generating 3D integral imaging frames is proposed. The method is based on a 3D integral imaging ray-tracer containing 3D integral imaging parser, 3D camera model, and a 3D integral imaging renderer.

Existing Machine Learning (ML) approaches known from the literature require the user to set and experimentally adjust parameters of a decision model to achieve the best result. When artificial neural networks (ANNs) are employed, a typical problem is setting of a proper network structure and learning parameters that are required to minimise possible overfitting. We propose a new evolutionary strategy of learning an ANN structure of a near-optimal connectivity from the given data and show that such structures are less prone to overfitting. The resultant ANN consists of a reasonably small number of neurons that are concisely described by a set of short-term polynomial functions of variables that make a distinct contribution to the output. The proposed technique has been tested on the ML benchmarks and the results showed that the performance is comparable with that obtained by the conventional ML methods that require ad hoc tuning.

Three dimensional (3D) integral imaging is a method that allows the display of full colour images with continuous parallax within a wide viewing zone. Due to the significant quantity of data required to represent a captured 3D integral image with high resolution, image compression becomes mandatory for the storage and transmission of integral images. This paper investigates the use of 2D discrete wavelet transform (2D-DWT) for the compression of omnidirectional 3D integral images (OII). The method requires the extraction of different viewpoint images from the integral image. A single viewpoint image is constructed by extracting one pixel from each microlens, then each viewpoint image is decomposed using a 2D-DWT. The resulting array of coefficients contains several frequency bands. The lower frequency bands of the viewpoint images are assembled and compressed using a 3D discrete cosine transform (3D-DCT) followed by Huffman coding. Whereas, the remaining higher bands are fed directly into a quantisation process followed by arithmetic coding. Simulations are performed on a set of several grey level 3D OII using a uniform scalar quantizer with deadzone. It was found that the algorithm achieves better rate-distortion performance and reconstructs the images with much better image quality at very low bit rates than previously reported 3D-DCT-based scheme. © 2007 Springer-Verlag London Limited.

All serial-serial multiplication structures previously reported in the literature have been confined to bit serial-serial multipliers. An architecture for digit serial-serial multipliers is presented. A set of designs are derived from the radix-2

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Abnormal patterns, existing e.g. in raw data, affect decision making process and have to be accurately detected and removed in order to reduce the risk of making wrong decisions. Existing Machine Learning (ML) approaches known from the literature require the user to set and experimentally adjust parameters of a decision model to achieve the best result. When artificial neural networks (ANNs) are employed, a typical problem is setting of a proper network structure and learning parameters that are required to minimise possible over-fitting. We propose a new evolutionary strategy of learning an ANN structure of a near optimal connectivity from the given data and show that such structures are less prone to over-fitting. The proposed method starts to learn with one input variable and one neuron and then adds a new input and a new neuron to the network while its validation error decreases. The resultant ANN consists of a reasonably small number of neurons that are concisely described by a set of short-term polynomial functions of variables that make a distinct contribution to the output. The proposed technique has been tested on the ML benchmarks and the results showed that the performance is comparable with that obtained by the conventional ML methods that require ad hoc tuning.

In this work, we present a bespoke assistive tool for people with severe visual disabilities. We are able to download text from books and present these books to our users in a virtual reality environment. This gives them specific capabilities to manipulate the text and factors such as brightness, size and contrast, in order for them to gain a comfortable reading experience.

Industrial control systems (ICSs) are integral parts of smart cities and critical to modern societies. Despite indisputable opportunities introduced by disruptor technologies, they proliferate the cybersecurity threat landscape, which is increasingly more hostile. The quantum of sensors utilized by ICS aided by artificial intelligence (AI) enables data collection capabilities to facilitate automation, process streamlining, and cost reduction. However, apart from the operational use, the sensors generated data combined with AI can be innovatively utilized to model anomalous behavior as part of layered security to increase resilience to cyberattacks. We introduce a framework to profile anomalous behavior in ICS and derive a cyber-risk score. A novel super learner ensemble for one-class classification is developed, using overlapping rolling windows with stratified, k -fold, n -repeat cross-validation applied to each base learner followed by majority voting to derive the best learner. Our approach is demonstrated on a liquid distribution sensor data set. The experimental results reveal that the proposed technique achieves an overall F1 -score of 99.13%, an anomalous recall score of 99% detecting anomalies lasting only 17 s. The key strength of the framework is the low computational complexity and error rate. The framework is modular, generic, applicable to other ICS, and transferable to other smart city sectors.

Digital twin technologies – comprised of data-rich models and machine learning – allow the operators of smart city applications to gain an accurate representation of complex cyber-physical models. However, the implicit need for resilient data protection must be achieved by integrating privacy-preserving mechanisms into the DT system design as part of an effective defence-in-depth strategy.

Abstract

Serious games and game‐based learning have received increased attention in recent years as an adjunct to teaching and learning material. This has been well echoed in the literature with numerous articles on the use of games and game theory in education. Despite this, no policy for the incorporation of serious games in education exists to date. This review paper draws from the literature to provide guideline recommendations that would help educators and policymakers in making the first step towards this.

Abstract

In this paper, a novel design for a metamaterial lens (superlens) based on a Photonic Crystal (PC) operating at visible wavelengths is reported. The proposed superlens consist of a gallium phosphide (GaP) dielectric slab waveguide with a hexagonal array of silver rods embedded within the GaP dielectric. In-house 2DFDTD numerical method is used to design and optimize the proposed superlens. Several superlenses are designed and integrated within a same dielectric platform, promoting the proof-of-concept (POC) of possible construction of an array of superlenses (or sub-lenses to create an M-Lens) for light field imaging applications. It is shown that the concavity of the superlens and positioning of each sub-lens within the array strongly affects the performances of the image in terms of resolution. Defects and various geometrical shapes are introduced to construct and optimize the proposed superlenses and increase the quality of the image resolution. It is shown that the orientation of the active region (ellipse) along x and y axis has tremendous influence on the quality of image resolution. In order to investigate the performance characteristics of the superlenses, transmitted power is calculated using 2D FDTD for image projections at various distances (in x and y plane). It is also shown, how the proposed superlens structures could be fabricated using standard micro fabrication techniques such as electron beam lithography, inductively coupled Reactive ion etching, and glancing angle evaporation methods. To the best of our knowledge, these are the first reported POC of superlenses, integrated in a monolithic platform suitable for high imaging resolution that can be used for light field imaging applications at visible wavelength. The proposed superlenses (integrated in a single platform M-Lens) will have tremendous impact on imaging applications.

In this paper, we report a unique multi-channel Photonic Crystal Fibre (PCF) sensor based on Surface Plasmon Resonance (SPR) structure comprising of silver and gold doped plasmonic layers for multi-Analyte sensing applications. We deployed a Full Vectorial Finite Element Method (FV-FEM) to investigate the sensitivity performance of the proposed PCF sensor. The SPR sensor is fully optimised to ensure propagation features, such as confinement loss, resonance condition, resolution and sensitivity are investigated within various optimised design parameters. According to spectral sensitivity analyses, 2500 nm/RIU and 3083 nm/RIU with 4 × 10

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We present our work on creating a virtual reality personal library environment to enable people with severe visual disabilities to engage in reading tasks. The environment acts as a personal study or library to an individual, who under other circumstances would not be able to access or use a public library or a physical study at home.We present tests undertaken to identify the requirements and needs of our users to inform this environment and finally present the working prototype.

In this paper, we aim to develop a low-computational system for real-time image processing and analysis in endoscopy images for the early detection of the human esophageal adenocarcinoma and colorectal cancer. Rich statistical features are used to train an improved machine-learning algorithm. Our algorithm can achieve a real-time classification of malign and benign cancer tumours with a significantly improved detection precision compared to the classical HOG method as a reference when it is implemented on real time embedded system NVIDIA TX2 platform. Our approach can help to avoid unnecessary biopsies for patients and reduce the over diagnosis of clinically insignificant cancers in the future.

Automatic speaker identification has become a challenging research problem due to its wide variety of applications. Neural networks and audio-visual identification systems can be very powerful, but they have limitations related to the number of speakers. The performance drops gradually as more and more users are registered with the system. This paper proposes a scalable algorithm for real-time text-independent speaker identification based on vowel recognition. Vowel formants are unique across different speakers and reflect the vocal tract information of a particular speaker. The contribution of this paper is the design of a scalable system based on vowel formant filters and a scoring scheme for classification of an unseen instance. Mel-Frequency Cepstral Coefficients (MFCC) and Linear Predictive Coding (LPC) have both been analysed for comparison to extract vowel formants by windowing the given signal. All formants are filtered by known formant frequencies to separate the vowel formants for further processing. The formant frequencies of each speaker are collected during the training phase. A test signal is also processed in the same way to find vowel formants and compare them with the saved vowel formants to identify the speaker for the current signal. A score-based scheme allows the speaker with the highest matching formants to own the current signal. This model requires less than 100 bytes of data to be saved for each speaker to be identified, and can identify the speaker within a second. Tests conducted on multiple databases show that this score-based scheme outperforms the back propagation neural network and Gaussian mixture models. Usually, the longer the speech files, the more significant were the improvements in accuracy.

Several novel radix iterative multiplication algorithms are presented. They can be used to design iterative array multipliers, serial/parallel multipliers and serial multipliers. Due to the iterative nature of the algorithms, the resulting structures are regular, modular and require localized communication only, which makes them suitable for VLSI implementation. The advantage of the structures based on the radix approach is that the architecture of the basic cell is not fixed for all radices. Any architecture can be used so long as its functionality satisfies the corresponding radix multiplication algorithm. The new algorithms can be used as a structured multiplier-design methodology that will allow designers to find the best compromise between hardware cost and multiplication time. In this approach, the multiplier architecture is first defined in terms of the radix-2nmultiplication algorithm which is general for all n. This results in an architecture being available for every n. The trade-off between cost and time is then achieved by choosing the radix that gives the best performance. © 1995 Taylor & Francis Ltd.

Real world information, obtained by humans is three dimensional (3-D). In experimental user-trials, subjective assessments have clearly demonstrated the increased impact of 3-D pictures compared to conventional flat-picture techniques. It is reasonable, therefore, that we humans want an imaging system that produces pictures that are as natural and real as things we see and experience every day. Three-dimensional imaging and hence, 3-D television (3DTV) are very promising approaches expected to satisfy these desires. Integral imaging, which can capture true 3D color images with only one camera, has been seen as the right technology to offer stress-free viewing to audiences of more than one person. In this paper, we propose a novel approach to use Evolutionary Strategy (ES) for joint motion and disparity estimation to compress 3D integral video sequences. We propose to decompose the integral video sequence down to viewpoint video sequences and jointly exploit motion and disparity redundancies to maximize the compression using a self adapted ES. A half pixel refinement algorithm is then applied by interpolating macro blocks in the previous frame to further improve the video quality. Experimental results demonstrate that the proposed adaptable ES with Half Pixel Joint Motion and Disparity Estimation can up to 1.5 dB objective quality gain without any additional computational cost over our previous algorithm.1Furthermore, the proposed technique get similar objective quality compared to the full search algorithm by reducing the computational cost up to 90%. © 2007 IEEE.

The paper presents two methods for the extraction of depth information from planar recorded data of 3D (three - dimensional) integral images. A description of the integral imaging system and the associated point spread function are presented. Depth estimation from 3D-integral pictures is formulated as an inverse problem of integral image formation. To cure the ill-posedness of the problem, approximate solutions are searched using so called 'regularization methods'. Two regularization schemes for obtaining constrained least-squares solutions are presented. The first algorithm is based on the projected Landweber method. The second method is a constrained version of Tikhonov's regularization method for illposed problems. Finally, illustrative simulation results are given. © 2008 IEEE.

Abstract

This research study explores the use of different lab material, investigating which types of materials contribute the most to the delivery and support of l aboratory ( l ab) sessions to design, skill‐based and technical courses in higher education in the UK . A qualitative research methodology was employed for this investigation and included both key stakeholders in academia, including 75 students and 12 tutors. An investigation was also conducted tracking student activity on the u niversity's e‐learning facility ( U ‐link). Our key findings indicate that overall electronic material is considered the most effective type of material for the delivery of a lab session. This is followed by print, video and lastly audio material according to student responses and video, print and audio material according to tutor responses. Student and tutor responses varied per individual module/subject area. Video material was regarded by students and tutors as the most effective type for the delivery of skill‐based lab sessions and generally for independent learning, and electronic material was regarded as the most effective type for the delivery of technical and design lab sessions. Lastly, student tracking revealed that the introduction of video lab material in two modules increased the average time spent by students on U ‐link by 58% for the technical module and 97% for the skill‐based module respectively.

A novel architecture for high performance two's complement digit-serial IIR filters is presented. The application of the digit-serial computation to the design of IIR filters introduces delay elements in the feedback loop of the IIR filter. This offers the possibility of pipelining the feedback loop inherent in the IIR filters. To fully explore the advantages offered by the use of digit-serial computation, the digit serial structure is based on the feed forward of the carry digit, which allows subdigit pipelining to increase the throughput rate of the IIR filters. A systematic design methodology is presented to derive a wide range of digit-serial IIR filter architectures which can be pipelined to the subdigit level. This will give designers greater flexibility in finding the best trade off between hardware cost and throughput rate. It is shown that the application of digit-serial computations for the realisation of IIR filters combined with the possibility of subdigit pipelining, results in an increase in the computation speed with a considerable reduction in silicon area consumption when compared to an equivalent bit-parallel IIR filter realisations. © 1998 Elsevier Science B.V. All rights reserved.

A new cell architecture for high performance digit-serial computation is presented. The design of this cell is based on the feed forward of the carry digit, which allows a high level of pipelining to increase the throughput rate with minimum latency. This will give designers greater flexibility in finding the best trade-off between hardware cost and throughput rate. A twin-pipe architecture to double the throughput rate of digit-serial/parallel multipliers is also presented. The effects of the number of pipelining levels and the twin architecture on the throughput rate and hardware cost are presented. A two's complement digit-serial/parallel multiplier which can operate on both negative and positive numbers is also presented. © 1993 Taylor & Francis Ltd.

Massive multi-input multioutput (MIMO) is believed to be an effective technique for future terrestrial broadcasting systems. Reciprocity calibration is one of the major practical challenges for massive MIMO systems operating in time-division duplexing mode. A new closed-loop reciprocity calibration method is investigated in this paper which can support online calibration with a higher accuracy compared to the existing methods. In the first part of the proposed method, an optimized relative calibration is introduced using the same structure of traditional relative calibration, but with less impaired hardware in the reference radio chain. In the second part, a test device (TD)-based calibration is proposed which makes online calibration possible. An experiment setup is built for the measurement of the base station hardware impairments and TD-based calibration implementation. Simulation results and the error vector magnitude of UE received signal after calibration show that the performance of our proposed method is improved significantly compared to the existing relative calibration methods.

In current local area networks, multimode fibers (MMFs), primarily graded index (GI) MMFs, are the main types of fibers employed for data communications. Due to their enormous bandwidth, it is considered that they are the main channel medium that can offer broadband multiservices using optical multiplexing techniques. Amongst these, mode group diversity multiplexing (MGDM) has been proposed as a way to integrate various services over an MMF network by exciting different groups of modes that can be used as independent and parallel communication channels. In this paper, we study optical multiple-input-multiple-output (O-MIMO) systems using MGDM techniques while also optimizing the launching conditions of light at the fiber inputs and the spot size, radial offset, angular offset, wavelength, and the radii of the segment areas of the detectors. We propose a new approach based on the optimization of launching and detection conditions in order to increase the capacity of an O-MIMO link using the MGDM technique. We propose a (3 \times 3) O-MIMO system, where our simulation results show significant improvement in GI MMFs' capacity compared with existing O-MIMO systems.

Integral imaging is a technique capable of displaying images with continuous parallax in full natural color. This paper presents a method of extracting depth map from integral images through viewpoint image extraction. The approach starts with the constructions of special viewpoint images frem the integral image. Each viewpoint image contains a two-dimensional parallel recording of the three-dimensional scene. A new mathematical expression giving the relationship between object depth and the corresponding viewpoint image pair displacement is derived by geometrically analyzing the integral recording process. The depth can be calculated from the corresponding displacement between two viewpoint images. A modified multibaseline algorithm, where the baseline is defined as the sample distance between two viewpoint images, is further adopted to integrate the information from multiple extracted viewpoint images. The developed depth extraction method is validated and applied to both real photographic and computer generated unidirectional integral images. The depth measuring solution gives a precise description of the object thickness with an error of less than 0.3% from the photographic image in the example. © 2005 SPIE and IS&T.

A novel approach is proposed to increase the throughput rate and reduce the hardware cost requirement of the linear systolic matrix-vector multiplication architecture for 2-D Fourier transform implementation. This is achieved by coding video signal/images more efficiently using 6-bit 1-D DPCM coding system prior to processing. It is shown that using 6-bit DPCM processing results in 64% improvement in speed and a significant saving in the hardware cost. The effect of quantisation errors on DPCM video signal/image Fourier transform is also presented.

A unique integral imaging system is employed as part of a three dimensional television system, allowing display of full colour 3D images with continuous parallax within a wide viewing zone. A significant quantity of data is required to represent captured integral 3D images with adequate resolution. A lossy compression scheme has been developed, based on the use of a three dimensional discrete cosine transform (3D-DCT), which makes possible efficient storage and transmission of such images while maintaining all information necessary to produce a high quality 3D display. In this paper we present the results of investigations into the design of quantization strategies to maximize rate-distortion performance, including the use of image-orientated optimization. Performance is vastly improved compared with that achieved using baseline JPEG for compression of full parallax integral 3D image data.

The current cost of bespoke clothing for significantly handicapped people or those with non-standard body shapes is too great for the vast majority of this growing population in the EC. The project aims to demonstrate that garments for the disabled and elderly can be produced both economically and profitably. We hope to be able to provide manufacturers with information on manufacturing methods enabling economic low cost production, and facilitate the distribution to consumers by making the information widely available throughout the world. The work consists of two main areas: (1) A database containing all information relating to specialized textiles and clothing for disabled and elderly people worldwide is being established. This knowledge is being gathered from manufacturers, retailers, industry, researchers and carers; it will be produced in a user-friendly form for this special group. We hope that this will open new niche production possibilities for manufacturers, with resulting economic advantage to disabled and elderly people. (2) As disabled and elderly persons often have body dimensions which differ from the norm, it is necessary to provide garments which fit specific individuals. It is proposed to do this efficiently by scanning individuals automatically to measure body shape and dimensions. Using a CAD/CAM system, the resulting data will generate patterns for the various components of a garment. These can then be cut from fabric and assembled into clothing. Some of the equipment required is already commercially available; the rest, including much software, will be produced during the project and integrated into a working system.

An adaptive 3D DCT based compression algorithm for use with full color unidirectional Integral 3D Images based on sub-sampling of the chrominance components is presented. Application of the algorithm to luminance and two chrominance components is discussed.

The current cost of bespoke clothing for significantly handicapped people or those with non-standard body shapes is too great for the vast majority of this growing population in the EC. The project aims to demonstrate that garments for the disabled and elderly can be produced both economically and profitably. We hope to be able to provide manufacturers with information on manufacturing methods enabling economic low cost production, and facilitate the distribution to consumers by making the information widely available throughout the world. The work consists of two main areas: (1) A database containing all information relating to specialized textiles and clothing for disabled and elderly people worldwide is being established. This knowledge is being gathered from manufacturers, retailers, industry, researchers and carers; it will be produced in a user-friendly form for this special group. We hope that this will open new niche production possibilities for manufacturers, with resulting economic advantage to disabled and elderly people. (2) As disabled and elderly persons often have body dimensions which differ from the norm, it is necessary to provide garments which fit specific individuals. It is proposed to do this efficiently by scanning individuals automatically to measure body shape and dimensions. Using a CAD/CAM system, the resulting data will generate patterns for the various components of a garment. These can then be cut from fabric and assembled into clothing. Some of the equipment required is already commercially available; the rest, including much software, will be produced during the project and integrated into a working system.

Light-field cameras play a vital role for rich 3D information retrieval in narrow range depth sensing applications. The key obstacle in composing light-fields from exposures taken by a plenoptic camera is to computationally calibrate, align and rearrange four-dimensional image data. Several attempts have been proposed to enhance the overall image quality by tailoring pipelines dedicated to particular plenoptic cameras and improving the consistency across viewpoints at the expense of high computational loads. The framework presented herein advances prior outcomes thanks to its novel micro image scale-space analysis for generic camera calibration independent of the lens specifications and its parallax-invariant, cost-effective viewpoint color equalization from optimal transport theory. Artifacts from the sensor and micro lens grid are compensated in an innovative way to enable superior quality in sub-aperture image extraction, computational refocusing and Scheimpflug rendering with sub-sampling capabilities. Benchmark comparisons using established image metrics suggest that our proposed pipeline outperforms state-of-the-art tool chains in the majority of cases. Results from a Wasserstein distance further show that our color transfer outdoes the existing transport methods. Our algorithms are released under an open-source license, offer cross-platform compatibility with few dependencies and different user interfaces. This makes the reproduction of results and experimentation with plenoptic camera technology convenient for peer researchers, developers, photographers, data scientists and others working in this field.

A method capable of capturing a full parallax 3D image suitable for television display, based on an advanced form of integral imaging is reported. The resolution requirements necessary for electronic capture and display of the full parallax, images are investigated and compared with those proposed for High Definition Television (HDTV). An experiment has been conducted to establish the minimum level of pixelation sufficient to display 3D images. The results and microphotographic pixelated images are presented. Several image compression techniques applied to the special case of integral imaging are considered, and a suitable compression strategy suggested.

The development of a compression algorithm for reduction of the transmission bit rate of 3D integral TV pictures is discussed. The proposed full parallax 3D image compression algorithm takes advantage of the cross correlation between the multiple images recorded on a CCD placed behind a directionally selective microlens array as well as the correlation inherent within each image. Tests carried out show that by using a hybrid DPCM/DCT coding scheme to code a still 3D integral TV image, high compression performance can be obtained while retaining all the necessary information to reconstruct a faithful duplicate of the original 3D image. A coding scheme for moving integral 3D images is also described.

Conventional integral three-dimensional images, either acquired by cameras or generated by computers, suffer from narrow viewing range. Many methods to enlarge the viewing range of integral images have been suggested. However, by far they all involve modifications of the optical systems, which normally make the system more complex and may bring other drawbacks in some designs. Based on the observation and study of the computer generated integral images, this paper quantitatively analyzes the viewing properties of the integral images in conventional configuration and its problem. To improve the viewing properties, a new model, the maximum viewing width (MVW) configuration is proposed. The MVW configured integral images can achieve the maximum viewing width on the viewing line at the optimum viewing distance and greatly extended viewing width around the viewing line without any modification of the original optical display systems. In normal applications, a MVW integral image also has better viewing zone transition properties than the conventional images. The considerations in the selection of optimal parameters are discussed. New definitions related to the viewing properties of integral images are given. Finally, two potential application schemes of the MVW integral images besides the computer generation are described. © 2005 SPIE and IS&T.