Dense light field coding: a survey

Light Field (LF) imaging is a promising solution for providing more immersive and closer to reality multimedia experiences to end-users with unprecedented creative freedom and flexibility for applications in different areas, such as virtual and augmented reality. Due to the recent technological advances in optics, sensor manufacturing and available transmission bandwidth, as well as the investment of many tech giants in this area, it is expected that soon many LF transmission systems will be available to both consumers and professionals. Recognizing this, novel standardization initiatives have recently emerged in both the Joint Photographic Experts Group (JPEG) and the Moving Picture Experts Group (MPEG), triggering the discussion on the deployment of LF coding solutions to efficiently handle the massive amount of data involved in such systems. Since then, the topic of LF content coding has become a booming research area, attracting the attention of many researchers worldwide. In this context, this paper provides a comprehensive survey of the most relevant LF coding solutions proposed in the literature, focusing on angularly dense LFs. Special attention is placed on a thorough description of the different LF coding methods and on the main concepts related to this relevant area. Moreover, comprehensive insights are presented into open research challenges and future research directions for LF coding.info:eu-repo/semantics/publishedVersio

Graph Spectral Image Processing

Recent advent of graph signal processing (GSP) has spurred intensive studies of signals that live naturally on irregular data kernels described by graphs (e.g., social networks, wireless sensor networks). Though a digital image contains pixels that reside on a regularly sampled 2D grid, if one can design an appropriate underlying graph connecting pixels with weights that reflect the image structure, then one can interpret the image (or image patch) as a signal on a graph, and apply GSP tools for processing and analysis of the signal in graph spectral domain. In this article, we overview recent graph spectral techniques in GSP specifically for image / video processing. The topics covered include image compression, image restoration, image filtering and image segmentation

Novel entropy coding and its application of the compression of 3D image and video signals

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThe broadcast industry is moving future Digital Television towards Super high resolution TV (4k or 8k) and/or 3D TV. This ultimately will increase the demand on data rate and subsequently the demand for highly efficient codecs. One of the techniques that researchers found it one of the promising technologies in the industry in the next few years is 3D Integral Image and Video due to its simplicity and mimics the reality, independently on viewer aid, one of the challenges of the 3D Integral technology is to improve the compression algorithms to adequate the high resolution and exploit the advantages of the characteristics of this technology. The research scope of this thesis includes designing a novel coding for the 3D Integral image and video compression. Firstly to address the compression of 3D Integral imaging the research proposes novel entropy coding which will be implemented first on 2D traditional images content in order to compare it with the other traditional common standards then will be applied on 3D Integra image and video. This approach seeks to achieve high performance represented by high image quality and low bit rate in association with low computational complexity. Secondly, new algorithm will be proposed in an attempt to improve and develop the transform techniques performance, initially by using a new adaptive 3D-DCT algorithm then by proposing a new hybrid 3D DWT-DCT algorithm via exploiting the advantages of each technique and get rid of the artifact that each technique of them suffers from. Finally, the proposed entropy coding will be further implemented to the 3D integral video in association with another proposed algorithm that based on calculating the motion vector on the average viewpoint for each frame. This approach seeks to minimize the complexity and reduce the speed without affecting the Human Visual System (HVS) performance. Number of block matching techniques will be used to investigate the best block matching technique that is adequate for the new proposed 3D integral video algorithm

Locally linear embedding-based prediction for 3D holoscopic image coding using HEVC

Holoscopic imaging is a prospective acquisition and display solution for providing true 3D content and fatigue-free 3D visualization. However, efficient coding schemes for this particular type of content are needed to enable proper storage and delivery of the large amount of data involved in these systems. Therefore, this paper proposes an alternative HEVC-based coding scheme for efficient representation of holoscopic images. In this scheme, some directional intra prediction modes of the HEVC are replaced by a more efficient prediction framework based on locally linear embedding techniques. Experimental results show the advantage of the proposed prediction for 3D holoscopic image coding, compared to the reference HEVC standard as well as previously presented approaches in this field.info:eu-repo/semantics/submittedVersio

Light field coding with field of view scalability and exemplar-based inter-layer prediction

Light field imaging based on microlens arrays—a.k.a. holoscopic, plenoptic, and integral imaging—has currently risen up as a feasible and prospective technology for future image and video applications. However, deploying actual light field applications will require identifying more powerful representations and coding solutions that support arising new manipulation and interaction functionalities. In this context, this paper proposes a novel scalable coding solution that supports a new type of scalability, referred to as field-of-view scalability. The proposed scalable coding solution comprises a base layer compliant with the High Efficiency Video Coding (HEVC) standard, complemented by one or more enhancement layers that progressively allow richer versions of the same light field content in terms of content manipulation and interaction possibilities. In addition, to achieve high-compression performance in the enhancement layers, novel exemplar-based interlayer coding tools are also proposed, namely: 1) a direct prediction based on exemplar texture samples from lower layers and 2) an interlayer compensated prediction using a reference picture that is built relying on an exemplar-based algorithm for texture synthesis. Experimental results demonstrate the advantages of the proposed scalable coding solution to cater to users with different preferences/requirements in terms of interaction functionalities, while providing better rate- distortion performance (independently of the optical setup used for acquisition) compared to HEVC and other scalable light field coding solutions in the literature.info:eu-repo/semantics/acceptedVersio

Overview of 3D Video: Coding Algorithms, Implementations and Standardization

Projecte final de carrera fet en col.laboració amb Linköping Institute of TechnologyEnglish: 3D technologies have aroused a great interest over the world in the last years. Television, cinema and videogames are introducing, little by little, 3D technologies into the mass market. This comes as a result of the research done in the 3D field, solving many of its limitations such as quality, contents creation or 3D displays. This thesis focus on 3D video, considering concepts that concerns the coding issues and the video formats. The aim is to provide an overview of the current state of 3D video, including the standardization and some interesting implementations and alternatives that exist. In the report necessary background information is presented in order to understand the concepts developed: compression techniques, the different video formats, their standardization and some advances or alternatives to the processes previously explained. Finally, a comparison between the different concepts is presented to complete the overview, ending with some conclusions and proposed ideas for future works.Castellano: Las tecnologías 3D han despertado un gran interés en todo el mundo en los últimos años. Televisión, cine y videojuegos están introduciendo, poco a poco, ésta tecnología en el mercado. Esto es resultado de la investigación realizada en el campo de las 3D, solucionando muchas de sus limitaciones, como la calidad, la creación de contenidos o las pantallas 3D. Este proyecto se centra en el video 3D, considerando los conceptos relacionados con la codificación y los formatos de vídeo. El objetivo es proporcionar una visión del estado actual del vídeo 3D, incluyendo los estándares y algunas de las implementaciones más interesantes que existen. En la memoria, se presenta información adicional para facilitar el seguimiento de los conceptos desarrollados: técnicas de compresión, formatos de vídeo, su estandarización y algunos avances o alternativas a los procesos explicados. Finalmente, se presentan diferentes comparaciones entre los conceptos tratados, acabando el documento con las conclusiones obtenidas e ideas propuestas para futuros trabajos.Català: Les tecnologies 3D han despertat un gran interès a tot el món en els últims anys. Televisió, cinema i videojocs estan introduint, lentament, aquesta tecnologia en el mercat. Això és resultat de la investigació portada a terme en el camp de les 3D, solucionant moltes de les seves limitacions, com la qualitat, la creació de continguts o les pantalles 3D. Aquest proyecte es centra en el video 3D, considerant els conceptes relacionats amb la codificació i els formats de video. L'objectiu és proporcionar una visió de l'estat actual del video 3D, incloent-hi els estandàrds i algunes de les implementacions més interessants que existeixen. A la memòria, es presenta informació adicional per facilitar el seguiment dels conceptes desenvolupats: tècniques de compressió, formats de video, la seva estandardització i alguns avenços o alternatives als procesos explicats. Finalment, es presenten diferents comparacions entre els conceptes tractats i les conclusions obtingudes, juntament amb propostes per a futurs treballs

Weighted bi-prediction for light field image coding

Light field imaging based on a single-tier camera equipped with a microlens array – also known as integral, holoscopic, and plenoptic imaging – has currently risen up as a practical and prospective approach for future visual applications and services. However, successfully deploying actual light field imaging applications and services will require developing adequate coding solutions to efficiently handle the massive amount of data involved in these systems. In this context, self-similarity compensated prediction is a non-local spatial prediction scheme based on block matching that has been shown to achieve high efficiency for light field image coding based on the High Efficiency Video Coding (HEVC) standard. As previously shown by the authors, this is possible by simply averaging two predictor blocks that are jointly estimated from a causal search window in the current frame itself, referred to as self-similarity bi-prediction. However, theoretical analyses for motion compensated bi-prediction have suggested that it is still possible to achieve further rate-distortion performance improvements by adaptively estimating the weighting coefficients of the two predictor blocks. Therefore, this paper presents a comprehensive study of the rate-distortion performance for HEVC-based light field image coding when using different sets of weighting coefficients for self-similarity bi-prediction. Experimental results demonstrate that it is possible to extend the previous theoretical conclusions to light field image coding and show that the proposed adaptive weighting coefficient selection leads to up to 5 % of bit savings compared to the previous self-similarity bi-prediction scheme.info:eu-repo/semantics/acceptedVersio

Light field image processing: an overview

Light field imaging has emerged as a technology allowing to capture richer visual information from our world. As opposed to traditional photography, which captures a 2D projection of the light in the scene integrating the angular domain, light fields collect radiance from rays in all directions, demultiplexing the angular information lost in conventional photography. On the one hand, this higher dimensional representation of visual data offers powerful capabilities for scene understanding, and substantially improves the performance of traditional computer vision problems such as depth sensing, post-capture refocusing, segmentation, video stabilization, material classification, etc. On the other hand, the high-dimensionality of light fields also brings up new challenges in terms of data capture, data compression, content editing, and display. Taking these two elements together, research in light field image processing has become increasingly popular in the computer vision, computer graphics, and signal processing communities. In this paper, we present a comprehensive overview and discussion of research in this field over the past 20 years. We focus on all aspects of light field image processing, including basic light field representation and theory, acquisition, super-resolution, depth estimation, compression, editing, processing algorithms for light field display, and computer vision applications of light field data

Light field image compression

Light field imaging based on a single-tier camera equipped with a micro-lens array has currently risen up as a practical and prospective approach for future visual applications and services. However, successfully deploying actual light field imaging applications and services will require identifying adequate coding solutions to efficiently handle the massive amount of data involved in these systems. In this context, this chapter presents some of the most recent light field image coding solutions that have been investigated. After a brief review of the current state of the art in image coding formats for light field photography, an experimental study of the rate-distortion performance for different coding formats and architectures is presented. Then, aiming at enabling faster deployment of light field applications and services in the consumer market, a scalable light field coding solution that provides backward compatibility with legacy display devices (e.g., 2D, 3D stereo, and 3D multiview) is also presented. Furthermore, a light field coding scheme based on a sparse set of microimages and the associated blockwise disparity is also presented. This coding scheme is scalable with three layers such that the rendering can be performed with the sparse micro-image set, the reconstructed light field image, and the decoded light field image.info:eu-repo/semantics/acceptedVersio