By Pankaj N. Topiwala
ISBN-10: 0306470438
ISBN-13: 9780306470431
ISBN-10: 0792381823
ISBN-13: 9780792381822
A thrilling new improvement has taken position within the electronic period that has captured the mind's eye and skill of researchers all over the world - wavelet snapshot compression. This know-how has deep roots in theories of imaginative and prescient, and provides functionality advancements over all different compression equipment, equivalent to these according to Fourier transforms, vectors quantizers, fractals, neural nets, and so on. it really is this progressive new expertise that's awarded in Wavelet picture and Video Compression, in a kind that's obtainable to the biggest viewers attainable. Wavelet photo and Video Compression is split into 4 elements. half I, heritage fabric, introduces the elemental mathematical constructions that underly photograph compression algorithms with the purpose of supplying a simple advent to the mathematical ideas which are must haves for the rest of the booklet. It explains such subject matters as switch of bases, scalar and vector quantization, bit allocation and rate-distortion conception, entropy coding, the discrete-cosine rework, wavelet filters and different similar issues. half II, nonetheless picture Coding, offers a spectrum of wavelet nonetheless photo coding recommendations. half III, precise subject matters in nonetheless snapshot Coding, offers various instance coding schemes with a different style in both method or software area. half IV, Video Coding, examines wavelet and pyramidal coding strategies for video facts. Wavelet snapshot and Video Compression serves as an exceptional reference and will be used as a textual content for complex classes overlaying the topic.
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Extra resources for Wavelet Image and Video Compression
Sample text
The spaces are made up of functions that are constant on smaller and smaller dyadic intervals (whose endpoints are rational numbers with denominators that are powers of 2). It is not hard to prove that any function can be approximated by a sequence of step functions whose step width shrinks to zero. And in the other direction, as it is easy to show that only the zero-function is locally constant on intervals whose width grows unbounded. These remarks indicate that axioms 1 to 3 are satisfied, while the others are by construction.
A two-channel perfect reconstruction filter bank. decomposition. The reconstruction process, then, must precisely duplicate the decomposition in reverse. Since the transformations are unitary at each step, the concatenation of unitary transformations is still unitary, and there is no loss of either energy or information in the process.
The wavelet transform seems to do an excellent job of that, since most of the subbands in the wavelet transformed image appear to be well-structured. , into the residual lowpass subband, see chap. 1, figure 5) – a phenomenon called energy compaction, while the rest of the data is very sparse and well-modelled, allows for its exploitation for compression. 4 References [1] A. Jain, Fundamentals of Digital Image Processing, Prentice-Hall, 1989. [2] D. Marr, Vision, W. H. , 1982. [3] J. Fourier, Theorie Analytique de la Chaleur, Gauthiers-Villars, Paris, 1888.