A family of stereoscopic image compression algorithms using wavelet transforms

With the standardization of JPEG-2000, wavelet-based image and video compression technologies are gradually replacing the popular DCT-based methods. In parallel to this, recent developments in autostereoscopic display technology is now threatening to revolutionize the way in which consumers are used to enjoying the traditional 2D display based electronic media such as television, computer and movies. However, due to the two-fold bandwidth/storage space requirement of stereoscopic imaging, an essential requirement of a stereo imaging system is efficient data compression. In this thesis, seven wavelet-based stereo image compression algorithms are proposed, to take advantage of the higher data compaction capability and better flexibility of wavelets. In the proposed CODEC I, block-based disparity estimation/compensation (DE/DC) is performed in pixel domain. However, this results in an inefficiency when DWT is applied on the whole predictive error image that results from the DE process. This is because of the existence of artificial block boundaries between error blocks in the predictive error image. To overcome this problem, in the remaining proposed CODECs, DE/DC is performed in the wavelet domain. Due to the multiresolution nature of the wavelet domain, two methods of disparity estimation and compensation have been proposed. The first method is performing DEJDC in each subband of the lowest/coarsest resolution level and then propagating the disparity vectors obtained to the corresponding subbands of higher/finer resolution. Note that DE is not performed in every subband due to the high overhead bits that could be required for the coding of disparity vectors of all subbands. This method is being used in CODEC II. In the second method, DEJDC is performed m the wavelet-block domain. This enables disparity estimation to be performed m all subbands simultaneously without increasing the overhead bits required for the coding disparity vectors. This method is used by CODEC III. However, performing disparity estimation/compensation in all subbands would result in a significant improvement of CODEC III. To further improve the performance of CODEC ill, pioneering wavelet-block search technique is implemented in CODEC IV. The pioneering wavelet-block search technique enables the right/predicted image to be reconstructed at the decoder end without the need of transmitting the disparity vectors. In proposed CODEC V, pioneering block search is performed in all subbands of DWT decomposition which results in an improvement of its performance. Further, the CODEC IV and V are able to perform at very low bit rates(< 0.15 bpp). In CODEC VI and CODEC VII, Overlapped Block Disparity Compensation (OBDC) is used with & without the need of coding disparity vector. Our experiment results showed that no significant coding gains could be obtained for these CODECs over CODEC IV & V. All proposed CODECs m this thesis are wavelet-based stereo image coding algorithms that maximise the flexibility and benefits offered by wavelet transform technology when applied to stereo imaging. In addition the use of a baseline-JPEG coding architecture would enable the easy adaptation of the proposed algorithms within systems originally built for DCT-based coding. This is an important feature that would be useful during an era where DCT-based technology is only slowly being phased out to give way for DWT based compression technology. In addition, this thesis proposed a stereo image coding algorithm that uses JPEG-2000 technology as the basic compression engine. The proposed CODEC, named RASTER is a rate scalable stereo image CODEC that has a unique ability to preserve the image quality at binocular depth boundaries, which is an important requirement in the design of stereo image CODEC. The experimental results have shown that the proposed CODEC is able to achieve PSNR gains of up to 3.7 dB as compared to directly transmitting the right frame using JPEG-2000

A family of stereoscopic image compression algorithms using wavelet transforms

With the standardization of JPEG-2000, wavelet-based image and video compression technologies are gradually replacing the popular DCT-based methods. In parallel to this, recent developments in autostereoscopic display technology is now threatening to revolutionize the way in which consumers are used to enjoying the traditional 2-D display based electronic media such as television, computer and movies. However, due to the two-fold bandwidth/storage space requirement of stereoscopic imaging, an essential requirement of a stereo imaging system is efficient data compression. In this thesis, seven wavelet-based stereo image compression algorithms are proposed, to take advantage of the higher data compaction capability and better flexibility of wavelets. [Continues.

Non-expansive symmetrically extended wavelet transform for arbitrarily shaped video object plane.

by Lai Chun Kit.Thesis (M.Phil.)--Chinese University of Hong Kong, 1998.Includes bibliographical references (leaves 68-70).Abstract also in Chinese.ACKNOWLEDGMENTS --- p.IVABSTRACT --- p.vChapter Chapter 1 --- Traditional Image and Video Coding --- p.1Chapter 1.1 --- Introduction --- p.1Chapter 1.2 --- Fundamental Principle of Compression --- p.1Chapter 1.3 --- Entropy - Value of Information --- p.2Chapter 1.4 --- Performance Measure --- p.3Chapter 1.5 --- Image Coding Overview --- p.4Chapter 1.5.1 --- Digital Image Formation --- p.4Chapter 1.5.2 --- Needs of Image Compression --- p.4Chapter 1.5.3 --- Classification of Image Compression --- p.5Chapter 1.5.4 --- Transform Coding --- p.6Chapter 1.6 --- Video Coding Overview --- p.8Chapter Chapter 2 --- Discrete Wavelets Transform (DWT) and Subband Coding --- p.11Chapter 2.1 --- Subband Coding --- p.11Chapter 2.1.1 --- Introduction --- p.11Chapter 2.1.2 --- Quadrature Mirror Filters (QMFs) --- p.12Chapter 2.1.3 --- Subband Coding for Image --- p.13Chapter 2.2 --- Discrete Wavelets Transformation (DWT) --- p.15Chapter 2.2.1 --- Introduction --- p.15Chapter 2.2.2 --- Wavelet Theory --- p.15Chapter 2.2.3 --- Comparison Between Fourier Transform and Wavelet Transform --- p.16Chapter Chapter 3 --- Non-expansive Symmetric Extension --- p.19Chapter 3.1 --- Introduction --- p.19Chapter 3.2 --- Types of extension scheme --- p.19Chapter 3.3 --- Non-expansive Symmetric Extension and Symmetric Sub-sampling --- p.21Chapter Chapter 4 --- Content-based Video Coding in MPEG-4 Purposed Standard --- p.24Chapter 4.1 --- Introduction --- p.24Chapter 4.2 --- Motivation of the new MPEG-4 standard --- p.25Chapter 4.2.1 --- Changes in the production of audio-visual material --- p.25Chapter 4.2.2 --- Changes in the consumption of multimedia information --- p.25Chapter 4.2.3 --- Reuse of audio-visual material --- p.26Chapter 4.2.4 --- Changes in mode of implementation --- p.26Chapter 4.3 --- Objective of MPEG-4 standard --- p.27Chapter 4.4 --- Technical Description of MPEG-4 --- p.28Chapter 4.4.1 --- Overview of MPEG-4 coding system --- p.28Chapter 4.4.2 --- Shape Coding --- p.29Chapter 4.4.3 --- Shape Adaptive Texture Coding --- p.33Chapter 4.4.4 --- Motion Estimation and Compensation (ME/MC) --- p.35Chapter Chapter 5 --- Shape Adaptive Wavelet Transformation Coding Scheme (SA WT) --- p.36Chapter 5.1 --- Shape Adaptive Wavelet Transformation --- p.36Chapter 5.1.1 --- Introduction --- p.36Chapter 5.1.2 --- Description of Transformation Scheme --- p.37Chapter 5.2 --- Quantization --- p.40Chapter 5.3 --- Entropy Coding --- p.42Chapter 5.3.1 --- Introduction --- p.42Chapter 5.3.2 --- Stack Run Algorithm --- p.42Chapter 5.3.3 --- ZeroTree Entropy (ZTE) Coding Algorithm --- p.45Chapter 5.4 --- Binary Shape Coding --- p.49Chapter Chapter 6 --- Simulation --- p.51Chapter 6.1 --- Introduction --- p.51Chapter 6.2 --- SSAWT-Stack Run --- p.52Chapter 6.3 --- SSAWT-ZTR --- p.53Chapter 6.4 --- Simulation Results --- p.55Chapter 6.4.1 --- SSAWT - STACK --- p.55Chapter 6.4.2 --- SSAWT ´ؤ ZTE --- p.56Chapter 6.4.3 --- Comparison Result - Cjpeg and Wave03. --- p.57Chapter 6.5 --- Shape Coding Result --- p.61Chapter 6.6 --- Analysis --- p.63Chapter Chapter 7 --- Conclusion --- p.64Appendix A: Image Segmentation --- p.65Reference --- p.6

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

The 1993 Space and Earth Science Data Compression Workshop

The Earth Observing System Data and Information System (EOSDIS) is described in terms of its data volume, data rate, and data distribution requirements. Opportunities for data compression in EOSDIS are discussed

State of the art in 2D content representation and compression

Livrable D1.3 du projet ANR PERSEECe rapport a été réalisé dans le cadre du projet ANR PERSEE (n° ANR-09-BLAN-0170). Exactement il correspond au livrable D3.1 du projet

Signal processing for high-definition television

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 1995.Includes bibliographical references (p. 60-62).by Peter Monta.Ph.D

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