Denoising and Compression S. Grace Chang, Bin Yu, and Martin Vetterli This...  Home/Search
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Abstract: The first part of this paper proposes an adaptive, data-driven threshold for image denoising via wavelet soft-thresholding. The threshold is derived in a Bayesian framework, and the prior used on the wavelet coefficients is the Generalized Gaussian distribution widely used in image processing applications. The proposed threshold is simple and closed-form, and it is adaptive to each subband because it depends on data-driven estimates of the parameters. Experimental results show that the... (Update)
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BibTeX entry: (Update)
@misc{ denoising-submitted,
author = "Denoising And Compression",
title = "SUBMITTED TO IEEE TRANSACTIONS ON IMAGE PROCESSING 1 Adaptive Wavelet Thresholding
for Image",
url = "citeseer.ist.psu.edu/756968.html" }
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