Wavelet domain image denoising for non-stationary noise and signal-dependent noise

被引：27
|
作者：
Goossens, Bart [1 ]
Pizurica, Aleksandra [1 ]
Philips, Wilfried [1 ]
机构：
[1] Univ Ghent, Dept Telecommun & Informat Proc, Sint Pietersnieuwstr 41, B-9000 Ghent, Belgium
来源：
2006 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP 2006, PROCEEDINGS | 2006年
关键词：
image restoration; Gaussian noise; non-stationary noise; signal-dependent noise;
D O I：
10.1109/ICIP.2006.312694
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We develop a low-complexity overcomplete wavelet domain method for denoising digital images corrupted with non-stationary white additive Gaussian noise. The noise level for each pixel is estimated from a local window around that pixel. We use a shrinkage function that adapts itself to the noise level and to the spatially changing statistics of the image. Experiments show that this noise model has good results for different non-stationary noise sources. Finally, we extend our method for denoising images corrupted with signal-dependent noise.
引用
收藏
页码：1425 / +
页数：3
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