Title :
A new image denoising algorithm based on nonsubsampled contourlet transform
Author :
Song, Haohao ; Gu, Jian
Author_Institution :
MPS Quality Supervision & Testing Center of Security Products for Comput. Inf. Syst., Shanghai, China
Abstract :
A new postprocessing method based on nonsubsampled contourlet transform is introduced in this paper for suppressing additive Gaussian Noise (AWGN) in images. By transforming the noised image into nonsubsampled contourlet domain, the lowest-frequency subband is filtered by wiener filter firstly. According to the adaptive thresholds, the contourlet coefficients in different subbands are filtered. Experimental results show that our image denoising algorithm achieves the better performance than the traditional wiener filter method and the denoising algorithms based on wavelet or contourlet.
Keywords :
AWGN; Wiener filters; filtering theory; image denoising; wavelet transforms; AWGN; Wiener filter; adaptive thresholds; additive Gaussian noise suppression; contourlet coefficients; image denoising algorithm; lowest-frequency subband filtering; nonsubsampled contourlet transform; postprocessing method; wavelet transform; AWGN; Filtering algorithms; Image denoising; Wavelet transforms; Wiener filters;
Conference_Titel :
Audio, Language and Image Processing (ICALIP), 2012 International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4673-0173-2
DOI :
10.1109/ICALIP.2012.6376662