context modeling for image denoising S. Grace Chang, Bin Yu, and Martin...  Home/Search
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Abstract: The method of wavelet thresholding for removing noise, or denoising, has been researched extensively due to its effectiveness and simplicity. Much of the literature has focused on developing the best uniform threshold or best basis selection. However, not much has been done to make the threshold values adaptive to the spatially changing statistics of images. Such adaptivity can improve the wavelet thresholding performance because it allows additional local information of the image (such as the... (Update)
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BibTeX entry: (Update)
@misc{ for-spatially,
author = "Context Modeling For",
title = "Spatially Adaptive Wavelet Thresholding With",
url = "citeseer.ist.psu.edu/756867.html" }
Citations (may not include all citations):1526 Ten Lectures on Wavelets (context) - Daubechies - 1992
1064 A theory for multiresolution signal decomposition: The wavel.. (context) - Mallat - 1989
282 Wavelets and Subband Coding (context) - Vetterli, Kovacevi'c - 1995
243 Ideal spatial adaptation via wavelet shrinkage (context) - Donoho, Johnstone - 1994
156 Translation-invariant de-noising - Coifman, Donoho - 1995
127 Wavelet threshold estimators for data with correlated noise - Johnstone, Silverman - 1997
109 Image coding based on mixture modeling of wavelet coefficien.. - LoPresto, Ramchandran et al. - 1997
32 An optimal bit allocation algorithm for sub-band coding (context) - Westerink, Biemond et al. - 1987
14 Image Denoising via Lossy Compression and Wavelet Thresholdi.. - Chang, Yu et al. - 1997
11 Adapting for heteroscedasticity in linear models (context) - Carroll - 1982
6 Image Subband Coding using Progressive Classification and Ad.. - Yoo, Ortega et al. - 1997
6 Estimation of heteroscedasticity in regression analysis (context) - Muller, Stadtmuller - 1987
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