Data compression systems for home-use digital video recording

The authors focus on image data compression techniques for digital recording. Image coding for storage equipment covers a large variety of systems because the applications differ considerably in nature. Video coding systems suitable for digital TV and HDTV recording and digital electronic still picture storage are considered. In addition, attention is paid to picture coding for interactive systems, such as the compact-disc interactive system. The relation between the recording system boundary conditions and the applied coding techniques is outlined. The main emphasis is on picture coding techniques for digital consumer recordin

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

Visual Data Compression for Multimedia Applications

The compression of visual information in the framework of multimedia applications is discussed. To this end, major approaches to compress still as well as moving pictures are reviewed. The most important objective in any compression algorithm is that of compression efficiency. High-compression coding of still pictures can be split into three categories: waveform, second-generation, and fractal coding techniques. Each coding approach introduces a different artifact at the target bit rates. The primary objective of most ongoing research in this field is to mask these artifacts as much as possible to the human visual system. Video-compression techniques have to deal with data enriched by one more component, namely, the temporal coordinate. Either compression techniques developed for still images can be generalized for three-dimensional signals (space and time) or a hybrid approach can be defined based on motion compensation. The video compression techniques can then be classified into the following four classes: waveform, object-based, model-based, and fractal coding techniques. This paper provides the reader with a tutorial on major visual data-compression techniques and a list of references for further information as the details of each metho

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

Study and simulation of low rate video coding schemes

The semiannual report is included. Topics covered include communication, information science, data compression, remote sensing, color mapped images, robust coding scheme for packet video, recursively indexed differential pulse code modulation, image compression technique for use on token ring networks, and joint source/channel coder design

Image compression using noncausal prediction

Image compression commonly is achieved using prediction of the value of pixels from surrounding pixels. Normally the choice of pixels used in the prediction is restricted to previously scanned pixels. A better prediction can be achieved if pixels on all sides of the pixel to be predicted are used. A prediction and decoding method is proposed that is independent of scanning order of the image. The decoding process makes use of an iterative decoder. A sequence of images is generated that converges to a final image that is identical to the original image. The theory underlying noncausal prediction and iterative decoding is developed. Convergence properties of the decoding algorithm are studied and conditions for convergence are presented. Distortions to the prediction residual after encoding can be caused by storage requirements, such as quantization and compression and also by errors in transmission. Effects of distortions of the residual on the final decoded image are investigated by introducing several types of distortion of the residual, including (1) alteration of randomly selected bits in the residual, (2) addition of a sinusoidal signal to the residual, (3) quantization of the residual and (4) compression of the residual using lossy Haar wavelet coding. The resulting distortion in the decoded images was generally less for noncausal prediction than for causal prediction, both in terms of PSNR and visual quality. Most noticeably, the streaks found in the decoded Image after causal encoding were absent with noncausal encoding

Motion compensated interpolation for subband coding of moving images

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.Includes bibliographical references (leaves 108-119).by Mark Daniel Polomski.M.S