Stack-run adaptive wavelet image compression

We report on the development of an adaptive wavelet image coder based on stack-run representation of the quantized coefficients. The coder works by selecting an optimal wavelet packet basis for the given image and encoding the quantization indices for significant coefficients and zero runs between coefficients using a 4-ary arithmetic coder. Due to the fact that our coder exploits the redundancies present within individual subbands, its addressing complexity is much lower than that of the wavelet zerotree coding algorithms. Experimental results show coding gains of up to 1:4dB over the benchmark wavelet coding algorithm

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

Implementation of wavelet codec by using Texas Instruments DSP TMS320C6701 EVM board

This paper describes the implementation of the wavelet codec: (encoder and decoder) by using the Texas Instruments DSP (digital signal processor) TMS320C6701 on the EVM (evaluation module) board. The wavelet codec is used to compress and decompress gray scale images for real time data compression. The wavelet codec algorithm has been transferred into C and assembly code in the Code Composer Studio in order to program the 'C6xx DSP. The capability of the 'C6xx to change the code easily, correct or update applications, reduces the development time, cost and power consumption. With. the development tools provided for the 'C6xx DSP platform, it creates an easy-to-use environment that optimizes the devices' performance and minimizes technical barriers to software and hardware desig

Fast Random Access to Wavelet Compressed Volumetric Data Using Hashing

We present a new approach to lossy storage of the coefficients of wavelet transformed data. While it is common to store the coefficients of largest magnitude (and let all other coefficients be zero), we allow a slightly different set of coefficients to be stored. This brings into play a recently proposed hashing technique that allows space efficient storage and very efficient retrieval of coefficients. Our approach is applied to compression of volumetric data sets. For the ``Visible Man'' volume we obtain up to 80% improvement in compression ratio over previously suggested schemes. Further, the time for accessing a random voxel is quite competitive

Wavelet Based Color Image Compression and Mathematical Analysis of Sign Entropy Coding

International audienceOne of the advantages of the Discrete Wavelet Transform (DWT) compared to Fourier Transform (e.g. Discrete Cosine Transform DCT) is its ability to provide both spatial and frequency localization of image energy. However, WT coefficients, like DCT coefficients, are defined by magnitude as well as sign. While algorithms exist for the coding of wavelet coefficients magnitude, there are no efficient for coding their sign. In this paper, we propose a new method based on separate entropy coding of sign and magnitude of wavelet coefficients. The proposed method is applied to the standard color test images Lena, Peppers, and Mandrill. We have shown that sign information of wavelet coefficients as well for the luminance as for the chrominance, and the refinement information of the quantized wavelet coefficients may not be encoded by an estimated probability of 0.5. The proposed method is evaluated; the results obtained are compared to JPEG2000 and SPIHT codec. We have shown that the proposed method has significantly outperformed the JPEG2000 and SPIHT codec as well in terms of PSNR as in subjective quality. We have proved, by an original mathematical analysis of the entropy, that the proposed method uses a minimum bit allocation in the sign information coding

High ratio wavelet video compression through real-time rate-distortion estimation.

Thesis (M.Sc.Eng.)-University of Natal, Durban, 2003.The success of the wavelet transform in the compression of still images has prompted an expanding effort to exercise this transform in the compression of video. Most existing video compression methods incorporate techniques from still image compression, such techniques being abundant, well defined and successful. This dissertation commences with a thorough review and comparison of wavelet still image compression techniques. Thereafter an examination of wavelet video compression techniques is presented. Currently, the most effective video compression system is the DCT based framework, thus a comparison between these and the wavelet techniques is also given. Based on this review, this dissertation then presents a new, low-complexity, wavelet video compression scheme. Noting from a complexity study that the generation of temporally decorrelated, residual frames represents a significant computational burden, this scheme uses the simplest such technique; difference frames. In the case of local motion, these difference frames exhibit strong spatial clustering of significant coefficients. A simple spatial syntax is created by splitting the difference frame into tiles. Advantage of the spatial clustering may then be taken by adaptive bit allocation between the tiles. This is the central idea of the method. In order to minimize the total distortion of the frame, the scheme uses the new p-domain rate-distortion estimation scheme with global numerical optimization to predict the optimal distribution of bits between tiles. Thereafter each tile is independently wavelet transformed and compressed using the SPIHT technique. Throughout the design process computational efficiency was the design imperative, thus leading to a real-time, software only, video compression scheme. The scheme is finally compared to both the current video compression standards and the leading wavelet schemes from the literature in terms of computational complexity visual quality. It is found that for local motion scenes the proposed algorithm executes approximately an order of magnitude faster than these methods, and presents output of similar quality. This algorithm is found to be suitable for implementation in mobile and embedded devices due to its moderate memory and computational requirements

High-performance compression of visual information - A tutorial review - Part I : Still Pictures

Digital images have become an important source of information in the modern world of communication systems. In their raw form, digital images require a tremendous amount of memory. Many research efforts have been devoted to the problem of image compression in the last two decades. Two different compression categories must be distinguished: lossless and lossy. Lossless compression is achieved if no distortion is introduced in the coded image. Applications requiring this type of compression include medical imaging and satellite photography. For applications such as video telephony or multimedia applications, some loss of information is usually tolerated in exchange for a high compression ratio. In this two-part paper, the major building blocks of image coding schemes are overviewed. Part I covers still image coding, and Part II covers motion picture sequences. In this first part, still image coding schemes have been classified into predictive, block transform, and multiresolution approaches. Predictive methods are suited to lossless and low-compression applications. Transform-based coding schemes achieve higher compression ratios for lossy compression but suffer from blocking artifacts at high-compression ratios. Multiresolution approaches are suited for lossy as well for lossless compression. At lossy high-compression ratios, the typical artifact visible in the reconstructed images is the ringing effect. New applications in a multimedia environment drove the need for new functionalities of the image coding schemes. For that purpose, second-generation coding techniques segment the image into semantically meaningful parts. Therefore, parts of these methods have been adapted to work for arbitrarily shaped regions. In order to add another functionality, such as progressive transmission of the information, specific quantization algorithms must be defined. A final step in the compression scheme is achieved by the codeword assignment. Finally, coding results are presented which compare stateof- the-art techniques for lossy and lossless compression. The different artifacts of each technique are highlighted and discussed. Also, the possibility of progressive transmission is illustrated

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