MASCOT : metadata for advanced scalable video coding tools : final report

The goal of the MASCOT project was to develop new video coding schemes and tools that provide both an increased coding efficiency as well as extended scalability features compared to technology that was available at the beginning of the project. Towards that goal the following tools would be used: - metadata-based coding tools; - new spatiotemporal decompositions; - new prediction schemes. Although the initial goal was to develop one single codec architecture that was able to combine all new coding tools that were foreseen when the project was formulated, it became clear that this would limit the selection of the new tools. Therefore the consortium decided to develop two codec frameworks within the project, a standard hybrid DCT-based codec and a 3D wavelet-based codec, which together are able to accommodate all tools developed during the course of the project

Fully Scalable Video Coding Using Redundant-Wavelet Multihypothesis and Motion-Compensated Temporal Filtering

In this dissertation, a fully scalable video coding system is proposed. This system achieves full temporal, resolution, and fidelity scalability by combining mesh-based motion-compensated temporal filtering, multihypothesis motion compensation, and an embedded 3D wavelet-coefficient coder. The first major contribution of this work is the introduction of the redundant-wavelet multihypothesis paradigm into motion-compensated temporal filtering, which is achieved by deploying temporal filtering in the domain of a spatially redundant wavelet transform. A regular triangle mesh is used to track motion between frames, and an affine transform between mesh triangles implements motion compensation within a lifting-based temporal transform. Experimental results reveal that the incorporation of redundant-wavelet multihypothesis into mesh-based motion-compensated temporal filtering significantly improves the rate-distortion performance of the scalable coder. The second major contribution is the introduction of a sliding-window implementation of motion-compensated temporal filtering such that video sequences of arbitrarily length may be temporally filtered using a finite-length frame buffer without suffering from severe degradation at buffer boundaries. Finally, as a third major contribution, a novel 3D coder is designed for the coding of the 3D volume of coefficients resulting from the redundant-wavelet based temporal filtering. This coder employs an explicit estimate of the probability of coefficient significance to drive a nonadaptive arithmetic coder, resulting in a simple software implementation. Additionally, the coder offers the possibility of a high degree of vectorization particularly well suited to the data-parallel capabilities of modern general-purpose processors or customized hardware. Results show that the proposed coder yields nearly the same rate-distortion performance as a more complicated coefficient coder considered to be state of the art

Motion Estimation and Compensation in the Redundant Wavelet Domain

Despite being the prefered approach for still-image compression for nearly a decade, wavelet-based coding for video has been slow to emerge, due primarily to the fact that the shift variance of the discrete wavelet transform hinders motion estimation and compensation crucial to modern video coders. Recently it has been recognized that a redundant, or overcomplete, wavelet transform is shift invariant and thus permits motion prediction in the wavelet domain. In this dissertation, other uses for the redundancy of overcomplete wavelet transforms in video coding are explored. First, it is demonstrated that the redundant-wavelet domain facilitates the placement of an irregular triangular mesh to video images, thereby exploiting transform redundancy to implement geometries for motion estimation and compensation more general than the traditional block structure widely employed. As the second contribution of this dissertation, a new form of multihypothesis prediction, redundant wavelet multihypothesis, is presented. This new approach to motion estimation and compensation produces motion predictions that are diverse in transform phase to increase prediction accuracy. Finally, it is demonstrated that the proposed redundant-wavelet strategies complement existing advanced video-coding techniques and produce significant performance improvements in a battery of experimental results

Colour image coding with wavelets and matching pursuit

This thesis considers sparse approximation of still images as the basis of a lossy compression system. The Matching Pursuit (MP) algorithm is presented as a method particularly suited for application in lossy scalable image coding. Its multichannel extension, capable of exploiting inter-channel correlations, is found to be an efficient way to represent colour data in RGB colour space. Known problems with MP, high computational complexity of encoding and dictionary design, are tackled by finding an appropriate partitioning of an image. The idea of performing MP in the spatio-frequency domain after transform such as Discrete Wavelet Transform (DWT) is explored. The main challenge, though, is to encode the image representation obtained after MP into a bit-stream. Novel approaches for encoding the atomic decomposition of a signal and colour amplitudes quantisation are proposed and evaluated. The image codec that has been built is capable of competing with scalable coders such as JPEG 2000 and SPIHT in terms of compression ratio

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

Motion Scalability for Video Coding with Flexible Spatio-Temporal Decompositions

PhDThe research presented in this thesis aims to extend the scalability range of the wavelet-based video coding systems in order to achieve fully scalable coding with a wide range of available decoding points. Since the temporal redundancy regularly comprises the main portion of the global video sequence redundancy, the techniques that can be generally termed motion decorrelation techniques have a central role in the overall compression performance. For this reason the scalable motion modelling and coding are of utmost importance, and specifically, in this thesis possible solutions are identified and analysed. The main contributions of the presented research are grouped into two interrelated and complementary topics. Firstly a flexible motion model with rateoptimised estimation technique is introduced. The proposed motion model is based on tree structures and allows high adaptability needed for layered motion coding. The flexible structure for motion compensation allows for optimisation at different stages of the adaptive spatio-temporal decomposition, which is crucial for scalable coding that targets decoding on different resolutions. By utilising an adaptive choice of wavelet filterbank, the model enables high compression based on efficient mode selection. Secondly, solutions for scalable motion modelling and coding are developed. These solutions are based on precision limiting of motion vectors and creation of a layered motion structure that describes hierarchically coded motion. The solution based on precision limiting relies on layered bit-plane coding of motion vector values. The second solution builds on recently established techniques that impose scalability on a motion structure. The new approach is based on two major improvements: the evaluation of distortion in temporal Subbands and motion search in temporal subbands that finds the optimal motion vectors for layered motion structure. Exhaustive tests on the rate-distortion performance in demanding scalable video coding scenarios show benefits of application of both developed flexible motion model and various solutions for scalable motion coding

A Survey of Signal Processing Problems and Tools in Holographic Three-Dimensional Television

Cataloged from PDF version of article.Diffraction and holography are fertile areas for application of signal theory and processing. Recent work on 3DTV displays has posed particularly challenging signal processing problems. Various procedures to compute Rayleigh-Sommerfeld, Fresnel and Fraunhofer diffraction exist in the literature. Diffraction between parallel planes and tilted planes can be efficiently computed. Discretization and quantization of diffraction fields yield interesting theoretical and practical results, and allow efficient schemes compared to commonly used Nyquist sampling. The literature on computer-generated holography provides a good resource for holographic 3DTV related issues. Fast algorithms to compute Fourier, Walsh-Hadamard, fractional Fourier, linear canonical, Fresnel, and wavelet transforms, as well as optimization-based techniques such as best orthogonal basis, matching pursuit, basis pursuit etc., are especially relevant signal processing techniques for wave propagation, diffraction, holography, and related problems. Atomic decompositions, multiresolution techniques, Gabor functions, and Wigner distributions are among the signal processing techniques which have or may be applied to problems in optics. Research aimed at solving such problems at the intersection of wave optics and signal processing promises not only to facilitate the development of 3DTV systems, but also to contribute to fundamental advances in optics and signal processing theory. © 2007 IEEE