Title :
Wavelet denoising in non gaussian noise using MDL principle
Author :
Xie, Jiecheng ; Zhang, Dali ; Xu, Wenli
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
Abstract :
Wavelet methods have succeeded in image denoising in gaussian noise. In non-gaussian noise, however, these methods will degrade drastically. By employing the MDL principle and a wavelet coefficient model, this paper discusses a study on image denoising in gaussian mixture noise. A new denoising scheme is derived and is based on per pixel detection. Experiment results show that the new scheme can not only denoise the image with small square error, but also provide a facility for the further compression.
Keywords :
data compression; image processing; noise; wavelet transforms; MDL principle; experiment results; gaussian mixture noise; image compression; image denoising; minimum description length; nongaussian noise; per pixel detection; small square error; wavelet coefficient model; wavelet denoising; Active noise reduction; Array signal processing; Automation; Degradation; Gaussian noise; Image coding; Image denoising; Noise reduction; Wavelet coefficients; Wavelet domain;
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
DOI :
10.1109/WCICA.2002.1021450