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

Locally adaptive vector quantization: Data compression with feature preservation

A study of a locally adaptive vector quantization (LAVQ) algorithm for data compression is presented. This algorithm provides high-speed one-pass compression and is fully adaptable to any data source and does not require a priori knowledge of the source statistics. Therefore, LAVQ is a universal data compression algorithm. The basic algorithm and several modifications to improve performance are discussed. These modifications are nonlinear quantization, coarse quantization of the codebook, and lossless compression of the output. Performance of LAVQ on various images using irreversible (lossy) coding is comparable to that of the Linde-Buzo-Gray algorithm, but LAVQ has a much higher speed; thus this algorithm has potential for real-time video compression. Unlike most other image compression algorithms, LAVQ preserves fine detail in images. LAVQ's performance as a lossless data compression algorithm is comparable to that of Lempel-Ziv-based algorithms, but LAVQ uses far less memory during the coding process

An Efficient Coding Method for Teleconferencing Video and Confocal Microscopic Image Sequences

In this paper we propose a three-dimensional vector quantization based video coding scheme. The algorithm uses a 3D vector quantization pyramidal code book based model with adaptive code book pyramidal codebook for compression. The pyramidal code book based model helps in getting high compression in case of modest motion. The adaptive vector quantization algorithm is used to train the code book for optimal performance with time. Some of the distinguished features of our algorithm are its excellent performance due to its adaptive behavior to the video composition and excellent compression due to codebook approach. We also propose an efficient codebook based post processing technique which enables the vector quantizer to possess higher correlation preservation property. Based on the special pattern of the codebook imposed by post-processing technique, a window based fast search (WBFS) algorithm is proposed. The WBFS algorithm not only accelerates the vector quantization processing, but also results in better rate-distortion performance. The proposed approach can be used for both teleconferencing videos and to compress images obtained from confocal laser scanning microscopy (CLSM). The results show that the proposed method gave higher subjective and objective image quality of reconstructed images at a better compression ratio and presented more acceptable results when applying image processing filters such as edge detection on reconstructed images. The experimental results demonstrate that the proposed method outperforms the teleconferencing compression standards H.261 and LBG based vector quantization technique

Data compression techniques applied to high resolution high frame rate video technology

An investigation is presented of video data compression applied to microgravity space experiments using High Resolution High Frame Rate Video Technology (HHVT). An extensive survey of methods of video data compression, described in the open literature, was conducted. The survey examines compression methods employing digital computing. The results of the survey are presented. They include a description of each method and assessment of image degradation and video data parameters. An assessment is made of present and near term future technology for implementation of video data compression in high speed imaging system. Results of the assessment are discussed and summarized. The results of a study of a baseline HHVT video system, and approaches for implementation of video data compression, are presented. Case studies of three microgravity experiments are presented and specific compression techniques and implementations are recommended

Vector quantization

During the past ten years Vector Quantization (VQ) has developed from a theoretical possibility promised by Shannon's source coding theorems into a powerful and competitive technique for speech and image coding and compression at medium to low bit rates. In this survey, the basic ideas behind the design of vector quantizers are sketched and some comments made on the state-of-the-art and current research efforts

Implementation issues in source coding

An edge preserving image coding scheme which can be operated in both a lossy and a lossless manner was developed. The technique is an extension of the lossless encoding algorithm developed for the Mars observer spectral data. It can also be viewed as a modification of the DPCM algorithm. A packet video simulator was also developed from an existing modified packet network simulator. The coding scheme for this system is a modification of the mixture block coding (MBC) scheme described in the last report. Coding algorithms for packet video were also investigated