Unconstrained Free-Viewpoint Video Coding

In this paper, we present a coding framework addressing image-space compression for free-viewpoint video. Our framework is based on time-varying 3D point samples which represent real-world objects. The 3D point samples are obtained after a geometrical reconstruction from multiple pre-recorded video sequences and thus allow for arbitrary viewpoints during playback. The encoding of the data is performed as an off-line process and is not time-critical. The decoding however, must support for real-time rendering of the dynamic 3D data. We introduce a compression framework which encodes multiple point attributes like depth and color into progressive streams. The reference data structure is aligned on the original camera input images and thus enables for easy view-dependent decoding. A novel differential coding approach permits random access in constant time throughout the entire data set and thus enables arbitrary viewpoint trajectories in both time and space.Engineering and Applied Science

3D Wavelet Transformation for Visual Data Coding With Spatio and Temporal Scalability as Quality Artifacts: Current State Of The Art

Several techniques based on the three–dimensional (3-D) discrete cosine transform (DCT) have been proposed for visual data coding. These techniques fail to provide coding coupled with quality and resolution scalability, which is a significant drawback for contextual domains, such decease diagnosis, satellite image analysis. This paper gives an overview of several state-of-the-art 3-D wavelet coders that do meet these requirements and mainly investigates various types of compression techniques those exists, and putting it all together for a conclusion on further research scope

Transformées basées graphes pour la compression de nouvelles modalités d’image

Due to the large availability of new camera types capturing extra geometrical information, as well as the emergence of new image modalities such as light fields and omni-directional images, a huge amount of high dimensional data has to be stored and delivered. The ever growing streaming and storage requirements of these new image modalities require novel image coding tools that exploit the complex structure of those data. This thesis aims at exploring novel graph based approaches for adapting traditional image transform coding techniques to the emerging data types where the sampled information are lying on irregular structures. In a first contribution, novel local graph based transforms are designed for light field compact representations. By leveraging a careful design of local transform supports and a local basis functions optimization procedure, significant improvements in terms of energy compaction can be obtained. Nevertheless, the locality of the supports did not permit to exploit long term dependencies of the signal. This led to a second contribution where different sampling strategies are investigated. Coupled with novel prediction methods, they led to very prominent results for quasi-lossless compression of light fields. The third part of the thesis focuses on the definition of rate-distortion optimized sub-graphs for the coding of omni-directional content. If we move further and give more degree of freedom to the graphs we wish to use, we can learn or define a model (set of weights on the edges) that might not be entirely reliable for transform design. The last part of the thesis is dedicated to theoretically analyze the effect of the uncertainty on the efficiency of the graph transforms.En raison de la grande disponibilité de nouveaux types de caméras capturant des informations géométriques supplémentaires, ainsi que de l'émergence de nouvelles modalités d'image telles que les champs de lumière et les images omnidirectionnelles, il est nécessaire de stocker et de diffuser une quantité énorme de hautes dimensions. Les exigences croissantes en matière de streaming et de stockage de ces nouvelles modalités d’image nécessitent de nouveaux outils de codage d’images exploitant la structure complexe de ces données. Cette thèse a pour but d'explorer de nouvelles approches basées sur les graphes pour adapter les techniques de codage de transformées d'image aux types de données émergents où les informations échantillonnées reposent sur des structures irrégulières. Dans une première contribution, de nouvelles transformées basées sur des graphes locaux sont conçues pour des représentations compactes des champs de lumière. En tirant parti d’une conception minutieuse des supports de transformées locaux et d’une procédure d’optimisation locale des fonctions de base , il est possible d’améliorer considérablement le compaction d'énergie. Néanmoins, la localisation des supports ne permettait pas d'exploiter les dépendances à long terme du signal. Cela a conduit à une deuxième contribution où différentes stratégies d'échantillonnage sont étudiées. Couplés à de nouvelles méthodes de prédiction, ils ont conduit à des résultats très importants en ce qui concerne la compression quasi sans perte de champs de lumière statiques. La troisième partie de la thèse porte sur la définition de sous-graphes optimisés en distorsion de débit pour le codage de contenu omnidirectionnel. Si nous allons plus loin et donnons plus de liberté aux graphes que nous souhaitons utiliser, nous pouvons apprendre ou définir un modèle (ensemble de poids sur les arêtes) qui pourrait ne pas être entièrement fiable pour la conception de transformées. La dernière partie de la thèse est consacrée à l'analyse théorique de l'effet de l'incertitude sur l'efficacité des transformées basées graphes

State-of-the-Art and Trends in Scalable Video Compression with Wavelet Based Approaches

3noScalable Video Coding (SVC) differs form traditional single point approaches mainly because it allows to encode in a unique bit stream several working points corresponding to different quality, picture size and frame rate. This work describes the current state-of-the-art in SVC, focusing on wavelet based motion-compensated approaches (WSVC). It reviews individual components that have been designed to address the problem over the years and how such components are typically combined to achieve meaningful WSVC architectures. Coding schemes which mainly differ from the space-time order in which the wavelet transforms operate are here compared, discussing strengths and weaknesses of the resulting implementations. An evaluation of the achievable coding performances is provided considering the reference architectures studied and developed by ISO/MPEG in its exploration on WSVC. The paper also attempts to draw a list of major differences between wavelet based solutions and the SVC standard jointly targeted by ITU and ISO/MPEG. A major emphasis is devoted to a promising WSVC solution, named STP-tool, which presents architectural similarities with respect to the SVC standard. The paper ends drawing some evolution trends for WSVC systems and giving insights on video coding applications which could benefit by a wavelet based approach.partially_openpartially_openADAMI N; SIGNORONI. A; R. LEONARDIAdami, Nicola; Signoroni, Alberto; Leonardi, Riccard

Self-similarity and wavelet forms for the compression of still image and video data

This thesis is concerned with the methods used to reduce the data volume required to represent still images and video sequences. The number of disparate still image and video coding methods increases almost daily. Recently, two new strategies have emerged and have stimulated widespread research. These are the fractal method and the wavelet transform. In this thesis, it will be argued that the two methods share a common principle: that of self-similarity. The two will be related concretely via an image coding algorithm which combines the two, normally disparate, strategies. The wavelet transform is an orientation selective transform. It will be shown that the selectivity of the conventional transform is not sufficient to allow exploitation of self-similarity while keeping computational cost low. To address this, a new wavelet transform is presented which allows for greater orientation selectivity, while maintaining the orthogonality and data volume of the conventional wavelet transform. Many designs for vector quantizers have been published recently and another is added to the gamut by this work. The tree structured vector quantizer presented here is on-line and self structuring, requiring no distinct training phase. Combining these into a still image data compression system produces results which are among the best that have been published to date. An extension of the two dimensional wavelet transform to encompass the time dimension is straightforward and this work attempts to extrapolate some of its properties into three dimensions. The vector quantizer is then applied to three dimensional image data to produce a video coding system which, while not optimal, produces very encouraging results

Low Bit-rate Color Video Compression using Multiwavelets in Three Dimensions

In recent years, wavelet-based video compressions have become a major focus of research because of the advantages that it provides. More recently, a growing thrust of studies explored the use of multiple scaling functions and multiple wavelets with desirable properties in various fields, from image de-noising to compression. In term of data compression, multiple scaling functions and wavelets offer a greater flexibility in coefficient quantization at high compression ratio than a comparable single wavelet. The purpose of this research is to investigate the possible improvement of scalable wavelet-based color video compression at low bit-rates by using three-dimensional multiwavelets. The first part of this work included the development of the spatio-temporal decomposition process for multiwavelets and the implementation of an efficient 3-D SPIHT encoder/decoder as a common platform for performance evaluation of two well-known multiwavelet systems against a comparable single wavelet in low bitrate color video compression. The second part involved the development of a motion-compensated 3-D compression codec and a modified SPIHT algorithm designed specifically for this codec by incorporating an advantage in the design of 2D SPIHT into the 3D SPIHT coder. In an experiment that compared their performances, the 3D motion-compensated codec with unmodified 3D SPIHT had gains of 0.3dB to 4.88dB over regular 2D wavelet-based motion-compensated codec using 2D SPIHT in the coding of 19 endoscopy sequences at 1/40 compression ratio. The effectiveness of the modified SPIHT algorithm was verified by the results of a second experiment in which it was used to re-encode 4 of the 19 sequences with lowest performance gains and improved them by 0.5dB to 1.0dB. The last part of the investigation examined the effect of multiwavelet packet on 3-D video compression as well as the effects of coding multiwavelet packets based on the frequency order and energy content of individual subbands

A DWT based perceptual video coding framework: concepts, issues and techniques

The work in this thesis explore the DWT based video coding by the introduction of a novel DWT (Discrete Wavelet Transform) / MC (Motion Compensation) / DPCM (Differential Pulse Code Modulation) video coding framework, which adopts the EBCOT as the coding engine for both the intra- and the inter-frame coder. The adaptive switching mechanism between the frame/field coding modes is investigated for this coding framework. The Low-Band-Shift (LBS) is employed for the MC in the DWT domain. The LBS based MC is proven to provide consistent improvement on the Peak Signal-to-Noise Ratio (PSNR) of the coded video over the simple Wavelet Tree (WT) based MC. The Adaptive Arithmetic Coding (AAC) is adopted to code the motion information. The context set of the Adaptive Binary Arithmetic Coding (ABAC) for the inter-frame data is redesigned based on the statistical analysis. To further improve the perceived picture quality, a Perceptual Distortion Measure (PDM) based on human vision model is used for the EBCOT of the intra-frame coder. A visibility assessment of the quantization error of various subbands in the DWT domain is performed through subjective tests. In summary, all these findings have solved the issues originated from the proposed perceptual video coding framework. They include: a working DWT/MC/DPCM video coding framework with superior coding efficiency on sequences with translational or head-shoulder motion; an adaptive switching mechanism between frame and field coding mode; an effective LBS based MC scheme in the DWT domain; a methodology of the context design for entropy coding of the inter-frame data; a PDM which replaces the MSE inside the EBCOT coding engine for the intra-frame coder, which provides improvement on the perceived quality of intra-frames; a visibility assessment to the quantization errors in the DWT domain

3D Wavelet-Based Video Codec with Human Perceptual Model

This thesis explores the use of a human perceptual model in video compression, channel coding, error concealment and subjective image quality measurement. The perceptual distortion model just-noticeable-distortion (JND) is investigated. A video encoding/decoding scheme based on 3D wavelet decomposition and the human perceptual model is implemented. It provides a prior compression quality control which is distinct from the conventional video coding system. JND is applied in quantizer design to improve the subjective quality ofcompressed video. The 3D wavelet decomposition helps to remove spatial and temporal redundancy and provides scalability of video quality. In order to conceal the errors that may occur under bad wireless channel conditions, a slicing method and a joint source channel coding scenario that combines RCPC with CRC and uses the distortion information toallocate convolutional coding rates are proposed. A new subjective quality index based on JND is proposed and used to evaluate the overall performance at different signal to noise ratios (SNR) and at different compression ratios.Due to the wide use of arithmetic coding (AC) in data compression, we consider it as a readily available unit in the video codec system for broadcasting. A new scheme for conditional access (CA) sub-system is designed based on the cryptographic property of arithmetic coding. Itsperformance is analyzed along with its application in a multi-resolution video compression system. This scheme simplifies the conditional access sub-system and provides satisfactory system reliability

Lifting transforms on graphs and their application to video coding

Compact representations of data are very useful in many applications such as coding, denoising or feature extraction. “Classical” transforms such as Discrete Cosine Transforms (DCT) or Discrete Wavelets Transforms (DWT) provide sparse approximations of smooth signals, but lose efficiency when they are applied to signals with large discontinuities. In such cases, directional transforms, which are able to adapt their basis functions to the underlying signal structure, improve the performance of “classical” transforms. In this PhD Thesis we describe a general class of lifting transforms on graphs that can be seen as N-dimensional directional transforms. Graphs are constructed so that every node corresponds to a specific sample point of a discrete N-dimensional signal and links between nodes represent correlation between samples. Therefore, non-correlated samples (e.g., samples across a large discontinuity in the signal) should not be linked. We propose a lifting-based directional transform that can be applied to any undirected graph. In this transform, filtering operations are performed following highcorrelation directions (indicated by the links between nodes), thus avoiding filtering across large discontinuities that give rise to large high-pass coefficients in those locations. In this way, the transform efficiently exploits the correlation that exists between data on the graph, leading to a more compact representation. We mainly focus on the design and optimization of these lifting transforms on graphs, studying and discussing the three main steps required to obtain an invertible and critically sampled transform: (i) graph construction, (ii) design of “good” graph bipartitions, and (iii) filter design. We also explain how to extend the transform to J levels of decomposition, obtaining a multiresolution analysis of the original N-dimensional signal. The proposed transform has many desirable properties, such as perfect reconstruction, critically-sampled, easy generalization to N-dimensional domains, non-separable and one-dimensional filtering operations, localization in frequency and in the original domain, and the ability to choose any filtering direction. As an application, we develop a graph-based video encoder where the goal is to obtain a compact representation of the original video sequence. To this end, we first propose a graph-representation of the video sequence and then design a 3-dimensional (spatio-temporal) non-separable directional transform. This can be viewed as an extension of wavelet transform-based video encoders that operate in the spatial and in the temporal domains independently. Our transform yields better compaction ability (in terms of non-linear approximation) than a state of the art motion-compensated temporal filtering transform (which can be interpreted as a temporal wavelet transform) and a comparable hybrid Discrete Cosine Transform (DCT)-based video encoder (which is the basis of the latest video coding standards). In order to obtain a complete video encoder, the transform coefficients and the side information (needed to obtain an invertible scheme) should be entropy coded and sent to the decoder. Therefore, we also propose a coefficient-reordering method based on the information of the graph which allows to improve the compression ability of the entropy encoder. Furthermore, we design two different low-cost approaches which aim to reduce the extensive computational complexity of the proposed system without causing significant losses of compression performance. The proposed complete system leads to an efficient encoder which significantly outperforms a comparable hybrid DCT-based encoder in rate-distortion terms. Finally, we investigate how rate-distortion optimization can be applied to the proposed coding scheme.La representación compacta de señales resulta útil en diversas aplicaciones, tales como compresión, reducción de ruido, o extracción de características. Transformadas “clásicas” como la Transformada Discreta del Coseno (DCT) o la TransformadaWavelet Discreta (DWT) logran aproximaciones compactas de señales suaves, pero pierden su eficiencia al ser aplicadas sobre se˜nales que contienen grandes discontinuidades. En estos casos, las transformadas direccionales, capaces de adaptar sus funciones base a la estructura de la señal a analizar, mejoran la eficiencia de las transformadas “clásicas”. En esta tesis nos centramos en el diseño y optimización de transformadas “lifting” sobre grafos, las cuales pueden ser interpretadas como transformadas direccionales N-dimensionales. Los grafos son construidos demanera que cada nodo se corresponde con una muestra específica de una señal discreta N-dimensional, y los enlaces entre los nodos representan correlación entre muestras. Así, muestras no correlacionadas (por ejemplo, muestras que se encuentran a ambos lados de una discontinuidad) no deberían estar unidas. Sobre el grafo formado aplicaremos transformadas basadas en el esquema “lifting”, en las que las operaciones de filtrado se realizan siguiendo las direcciones indicadas por los enlaces entre nodos (direcciones de alta correlación). De esta manera, evitaremos filtrar cruzando a través de largas discontinuidades (lo que resultaría en coeficientes con alto valor en dichas discontinuidades), dando lugar a una transformada direccional que explota la correlación que existe entre las muestras de la señal en el grafo, obteniendo una representación compacta de dicha señal. En esta tesis nos centramos, principalmente, en investigar los tres principales pasos requeridos para obtener una transformada direccional basada en el esquema “lifting” aplicado en grafos: (i) la construcción del grafo, (ii) el diseño de biparticiones del grafo, y (iii) la definición de los filtros. El buen diseño de estos tres procesos determinará, entre otras cosas, la capacidad para compactar la energía de la transformada. También explicamos cómo extender este tipo de transformadas a J niveles de descomposición, obteniendo un análisis multi-resolución de la señal N-dimensional original. La transformada propuesta tiene muchas propiedades deseables, tales como reconstrucción perfecta, muestreo crítico, fácil generalización a dominios N-dimensionales, operaciones de filtrado no separables y unidimensionales, localización en frecuencia y en el dominio original, y capacidad de elegir cualquier dirección de filtrado. Como aplicación, desarrollamos un codificador de vídeo basado en grafos donde el objetivo es obtener una versión compacta de la señal de vídeo original. Para ello, primero proponemos una representación en grafos de la secuencia de vídeo y luego diseñamos transformadas no separables direccionales 3-dimensionales (espacio-tiempo). Nuestro codificador puede interpretarse como una extensión de los codificadores de vídeo basados en “wavelets”, los cuales operan independientemente (de forma separable) en el dominio espacial y en el temporal. La transformada propuesta consigue mejores resultados (en términos de aproximación no lineal) que un método del estado del arte basado en “wavelets” temporales compensadas en movimiento, y un codificador DCT comparable (base de los últimos estándares de codificación de vídeo). Para conseguir un codificador de vídeo completo, los coeficientes resultantes de la transformada y la información secundaria (necesaria para obtener un esquema invertible) deben ser codificados entrópicamente y enviados al decodificador. Por ello, también proponemos en esta tesis un método de reordenación de los coeficientes basado en la información del grafo que permite mejorar la capacidad de compresión del codificador entrópico. El esquema de codificación propuesto mejora significativamente la eficiencia de un codificador híbrido basado en DCT en términos de tasa-distorsión. Sin embargo, nuestro método tiene la desventaja de su gran complejidad computacional. Para tratar de paliar este problema, diseñamos dos algoritmos que tratan de reducir dicha complejidad sin que ello afecte en la capacidad de compresión. Finalmente, investigamos como realizar optimización tasa-distorsión sobre el codificador basado en grafos propuesto