Digital Compression for Multimedia Engineering

This book is concerned with the image compression methods to advanced video coding algorithms & thus yields an exclusive, self-contained reference for practitioners to build a basis for future study, research, & development. It introduces image compression methods in the case of binary, gray scale, color palette, true color & video images. It works up from basic principles to the advanced video compression systems including MPEG 1, 2, 4 & 7, JPEG, H.261, H.263 & H.264/MPEG-4 AVC. Topics include fractal-based compression, statistical modeling, context modeling, Huffman coding, arithmetic coding, Colomb coding, transform-based modeling, run-length modeling, predictive modeling, progressive image decompression, vector quantization. Existing & forthcoming standards such as JBIG1, JBIG2, JPEG, JPEG-LS & JPEG-2000 are covered. For each algorithm, issues such as quality vs. bit rate vs. MSE and BPP, susceptibility to channel errors & implementation complexities are considered. It contains a lots of reconstructed & error images illustrating the outcome of each compression technique on a consistent image set, thus allowing for a direct assessment of bit rates & reconstructed image quality.

Autorentext

His long term research interest is in lossless data compression, both theoretically and in specific applications, such as lossless image compression, video codecs, wavelets, compressed sensing, remote sensing, error-resilient image and video transmission, optimization of video encoder, communications and internet related computing, encryption etc.