Image and Video Compression for Multimedia Engineering: by Yun Q. Shi, Huifang Sun

By Yun Q. Shi, Huifang Sun

Multimedia nonetheless can't accommodate the call for for giant quantities of visible information. with no the iteration of top quality video bitstreams, constrained functions will proceed to stifle the development of multimedia applied sciences. Thorough grounding in coding is required in order that purposes similar to MPEG-4 and JPEG 2000 may perhaps come to fruition.

Image and Video Compression for Multimedia Engineering offers an outstanding, complete figuring out of the basics and algorithms that bring about the construction of recent tools for producing top of the range video bit streams. The authors current a couple of correct advances in addition to overseas criteria.

New to the second one variation

·         A bankruptcy describing  the lately constructed video coding typical, MPEG-Part 10 Advances Video Coding sometimes called H.264

·         basic techniques and algorithms of JPEG2000

·         colour structures of electronic video

·         up to date video coding criteria and profiles

Visual facts, photo, and video coding will proceed to allow the construction of complicated undefined, compatible to the calls for of recent purposes. masking either photograph and video compression, this publication yields a different, self-contained reference for practitioners tobuild a foundation for destiny learn, learn, and development.

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Extra info for Image and Video Compression for Multimedia Engineering: Fundamentals, Algorithms, and Standards, Second Edition (Image Processing Series)

Example text

Finally, pulse code modulation (PCM), the best established and most frequently implemented digital coding method involving quantization, is described. 2 UNIFORM QUANTIZATION Uniform quantization is the simplest and most popular quantization technique. Conceptually, it is of great importance. Hence, we start our discussion on quantization with uniform quantization.

5 into the above two equations, we can express YIQ directly in terms of RGB. 10) YDbDr model — The YDbDr model is used in the SECAM (Sequential Couleur a Memoire) TV system. Note that SECAM is used in France, Russia, and some eastern European countries. The relationship between YDbDr and RGB appears below. 217¯ Ë B¯ (1. 13) YCbCr model — From the above, we can see that the U and V chrominance components are differences between the gamma-corrected color B and the luminance Y, and the gamma-corrected R and the luminance Y, respectively.

30, the information contained within a symbol is a logarithmic function of its occurrence probability. The smaller the probability, the more information the symbol contains. This agrees with common sense. The occurrence probability is somewhat related to the uncertainty of the symbol. A small occurrence probability means large uncertainty. In this way, we see that the information content of a symbol is about the uncertainty of the symbol. It is noted that the information measure defined here is valid for both equally probable symbols and nonequally probable symbols (Lathi, 1998).

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