Download 26.Image Processing by John G. Webster (Editor) PDF

By John G. Webster (Editor)

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I and II, Berlin: Springer Verlag, 1988 and references therein. 53. Special issues on photorefractive crystals, J. Opt. Soc. Amer. B: August 1988, August 1992, September 1994 and references therein. 54. P. Yeh Introduction to Photorefractive Nonlinear Optics, New York: Wiley, 1993. htm }{{}} ● HOME ● ABOUT US ● CONTACT US ● HELP Home / Engineering / Electrical and Electronics Engineering Wiley Encyclopedia of Electrical and Electronics Engineering Image and Video Coding Standard Article Kannan Ramchandran1, Mohammad Gharavi-Alkhansari1, Thomas S.

A basic fractal image coding algorithm. Computational Complexity. One major difficulty with fractal image coding is that the encoding process needs a lot of computation and requires a large amount of computer time. The main computations are trying every potential domain block, finding the best set of transformations for it, and computing how well the result matches the range block. However, there are techniques that alleviate this computational burden to some extent (6). The description given previously provides the basic mechanism of fractal coding.

However, to make effective use of any structure for improving coding performance, an algorithm requires a statistical characterization of the joint distribution of wavelet coefficients, capable of taking that structure into account. A hot research topic as of the late 1990s consists of identifying properties of the wavelet coefficients of images leading to good image-coding performance. , decorrelation), and the wavelet coefficients may be quantized and entropy coded similarly to the way DCT coefficients are used, taking this same approach ignores a fundamental wavelet property, the joint time-frequency localization.

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