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Noise removal via Bayesian wavelet coring

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2 Author(s)
Simoncelli, E.P. ; Dept. of Comput. & Inf. Sci., Pennsylvania Univ., Philadelphia, PA, USA ; Adelson, E.H.

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

Published in:

Image Processing, 1996. Proceedings., International Conference on  (Volume:1 )

Date of Conference:

16-19 Sep 1996

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