Download Blind Image Deconvolution: Theory and Applications by Patrizio Campisi, Karen Egiazarian PDF

By Patrizio Campisi, Karen Egiazarian

ISBN-10: 0849373670

ISBN-13: 9780849373671

Blind snapshot deconvolution is continually receiving expanding cognizance from the educational in addition the commercial international as a result of either its theoretical and functional implications. the sphere of blind photograph deconvolution has a number of purposes in several parts comparable to photograph recovery, microscopy, scientific imaging, organic imaging, distant sensing, astronomy, nondestructive checking out, geophysical prospecting, etc. Blind picture Deconvolution: conception and functions surveys the present country of analysis and perform as awarded via the main famous specialists within the box, therefore filling a spot within the to be had literature on blind picture deconvolution. discover the gamut of blind snapshot deconvolution methods and algorithms that at present exist and persist with the present study traits into the long run. This complete treatise discusses Bayesian concepts, unmarried- and multi-channel equipment, adaptive and multi-frame concepts, and a bunch of functions to multimedia processing, astronomy, distant sensing imagery, and clinical and organic imaging on the whole-body, small-part, and mobile degrees. every little thing you want to step into this dynamic box is at your fingertips during this certain, self-contained masterwork. For snapshot enhancement and recovery with out a priori details, flip to Blind photo Deconvolution: conception and purposes for the data and strategies you must take on real-world difficulties.

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Therefore the blur component should tend to dominate in the summation. It may be possible to remove this average image component, subtracting the average of a collection of representative unblurred images. 47), the Power Cepstrum may be used, which involves taking the ft of the log power spectra of the signals. Combined with the block-based method just described, the result is that a large spike will occur in the Cepstral domain wherever there was a periodic pattern of zeros in the original Fourier domain; the distance of this spike from the origin represents the spacing between the zeros and hence may be used to identify the parameters of the blurs.

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M. F. Tsumuraya and N. Baba, “Iterative blind deconvolution method using Lucy’s algorithm,” Astronomy and Astrophysics, vol. 282, no. 2, pp. 699–708, 1994. [89] B. C. McCallum, “Blind deconvolution by simulated annealing,” Optics Communications, vol. 75, no. 2, pp. 101–105, 1990. [90] D. Kundur and D. Hatzinakos, “A novel blind deconvolution scheme for image restoration using recursive filtering,” IEEE Transactions on Signal Processing, vol. 46, no. 2, pp. 375–390, 1998. [91] K. Nishi and S. Ando, “Blind superresolving image recovery from blurinvariant edges,” IEEE Transactions on Acoustic Speech, and Signal Processing, vol.

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