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Noise removal via Bayesian wavelet coring
Simoncelli, E.P.; Adelson, E.H.;
Image Processing, 1996. Proceedings., International Conference on
Volume 1,
16-19 Sept. 1996
Page(s):379
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382 vol.1
Abstract:
The classical solution to the noise removal problem is the Wiener filter, which utilizes the second-order statistics of the Fourier decomposition. Subband decompositions of natural images have significantly non-Gaussian higher-order point statistics; these statistics capture image properties that elude Fourier-based techniques. We develop a Bayesian estimator that is a natural extension of the Wiener solution, and that exploits these higher-order statistics. The resulting nonlinear estimator performs a “coring” operation. We provide a simple model for the subband statistics, and use it to develop a semi-blind noise removal algorithm based on a steerable wavelet pyramid
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