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

Efficient compression of motion compensated residuals

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Biorthogonality in lapped transforms : a study in high-quality audio compression

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (leaves 76-82).by Shiufun Cheung.Ph.D

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

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

Motion compensation and very low bit rate video coding

Recently, many activities of the International Telecommunication Union (ITU) and the International Standard Organization (ISO) are leading to define new standards for very low bit-rate video coding, such as H.263 and MPEG-4 after successful applications of the international standards H.261 and MPEG-1/2 for video coding above 64kbps. However, at very low bit-rate the classic block matching based DCT video coding scheme suffers seriously from blocking artifacts which degrade the quality of reconstructed video frames considerably. To solve this problem, a new technique in which motion compensation is based on dense motion field is presented in this dissertation. Four efficient new video coding algorithms based on this new technique for very low bit-rate are proposed. (1) After studying model-based video coding algorithms, we propose an optical flow based video coding algorithm with thresh-olding techniques. A statistic model is established for distribution of intensity difference between two successive frames, and four thresholds are used to control the bit-rate and the quality of reconstructed frames. It outperforms the typical model-based techniques in terms of complexity and quality of reconstructed frames. (2) An efficient algorithm using DCT coded optical flow. It is found that dense motion fields can be modeled as the first order auto-regressive model, and efficiently compressed with DCT technique, hence achieving very low bit-rate and higher visual quality than the H.263/TMN5. (3) A region-based discrete wavelet transform video coding algorithm. This algorithm implements dense motion field and regions are segmented according to their content significance. The DWT is applied to residual images region by region, and bits are adaptively allocated to regions. It improves the visual quality and PSNR of significant regions while maintaining low bit-rate. (4) A segmentation-based video coding algorithm for stereo sequence. A correlation-feedback algorithm with Kalman filter is utilized to improve the accuracy of optical flow fields. Three criteria, which are associated with 3-D information, 2-D connectivity and motion vector fields, respectively, are defined for object segmentation. A chain code is utilized to code the shapes of the segmented objects. it can achieve very high compression ratio up to several thousands

SPIHT image coding : analysis, improvements and applications.

Image compression plays an important role in image storage and transmission. In the popular Internet applications and mobile communications, image coding is required to be not only efficient but also scalable. Recent wavelet techniques provide a way for efficient and scalable image coding. SPIHT (set partitioning in hierarchical trees) is such an algorithm based on wavelet transform. This thesis analyses and improves the SPIHT algorithm. The preliminary part of the thesis investigates two-dimensional multi-resolution decomposition for image coding using the wavelet transform, which is reviewed and analysed systematically. The wavelet transform is implemented using filter banks, and the z-domain proofs are given for the key implementation steps. A scheme of wavelet transform for arbitrarily sized images is proposed. The statistical properties of the wavelet coefficients (being the output of the wavelet transform) are explored for natural images. The energy in the transform domain is localised and highly concentrated on the low-resolution subband. The wavelet coefficients are DC-biased, and the gravity centre of most octave-segmented value sections (which are relevant to the binary bit-planes) is offset by approximately one eighth of the section range from the geometrical centre. The intra-subband correlation coefficients are the largest, followed by the inter-level correlation coefficients in the middle then the trivial inter-subband correlation coefficients on the same resolution level. The statistical properties reveal the success of the SPIHT algorithm, and lead to further improvements. The subsequent parts of the thesis examine the SPIHT algorithm. The concepts of successive approximation quantisation and ordered bit-plane coding are highlighted. The procedure of SPIHT image coding is demonstrated with a simple example. A solution for arbitrarily sized images is proposed. Seven measures are proposed to improve the SPIHT algorithm. Three DC-level shifting schemes are discussed, and the one subtracting the geometrical centre in the image domain is selected in the thesis. The virtual trees are introduced to hold more wavelet coefficients in each of the initial sets. A scheme is proposed to reduce the redundancy in the coding bit-stream by omitting the predictable symbols. The quantisation of wavelet coefficients is offset by one eighth from the geometrical centre. A pre-processing technique is proposed to speed up the judgement of the significance of trees, and a smoothing is imposed on the magnitude of the wavelet coefficients during the pre-processing for lossy image coding. The optimisation of arithmetic coding is also discussed. Experimental results show that these improvements to SPIHT get a significant performance gain. The running time is reduced by up to a half. The PSNR (peak signal to noise ratio) is improved a lot at very low bit rates, up to 12 dB in the extreme case. Moderate improvements are also made at high bit rates. The SPIHT algorithm is applied to loss less image coding. Various wavelet transforms are evaluated for lossless SPIHT image coding. Experimental results show that the interpolating transform (4, 4) and the S+P transform (2+2, 2) are the best for natural images among the transforms used, the interpolating transform (4, 2) is the best for CT images, and the bi-orthogonal transform (9, 7) is always the worst. Content-based lossless coding of a CT head image is presented in the thesis, using segmentation and SPIHT. Although the performance gain is limited in the experiments, it shows the potential advantage of content-based image coding

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

Combined Industry, Space and Earth Science Data Compression Workshop

The sixth annual Space and Earth Science Data Compression Workshop and the third annual Data Compression Industry Workshop were held as a single combined workshop. The workshop was held April 4, 1996 in Snowbird, Utah in conjunction with the 1996 IEEE Data Compression Conference, which was held at the same location March 31 - April 3, 1996. The Space and Earth Science Data Compression sessions seek to explore opportunities for data compression to enhance the collection, analysis, and retrieval of space and earth science data. Of particular interest is data compression research that is integrated into, or has the potential to be integrated into, a particular space or earth science data information system. Preference is given to data compression research that takes into account the scien- tist's data requirements, and the constraints imposed by the data collection, transmission, distribution and archival systems

Discrete Wavelet Transforms

The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications