NDLI: Adaptive Shrinkage for Image Denoising Based on Contourlet Transform

Content Provider	IEEE Xplore Digital Library
Author	Kang Li Jinghuai Gao Wei Wang
Copyright Year	2008
Description	Author affiliation: Sch. of Electron. & Inf. Eng., Xi'an Jiaotong Univ., Xi'an (Kang Li; Jinghuai Gao; Wei Wang)
Abstract	We propose a new local adaptive shrinkage denoising approach based on the neighborhood characteristics of contourlet coefficients. Classical contourlet shrinkage denoising methods process the contourlet coefficients with a fixed threshold in each subband, without considering the clustering property of the coefficients. The shrinkage denoising method proposed in this paper determines the shrinkage threshold according to the neighboring contourlet coefficients, the scale of the coefficients and the noise level. Thus, the new threshold can preserve more significant coefficients that contain information of important singularity, and at the same time, attenuate more coefficients that contain information of noise when compared with the classical one. Our experiments show that the proposed shrinkage denoising method outperforms the classical contourlet shrinkage threshold method, in terms of both PSNR values and visual quality, especially for the images that include plentiful textures and edges.
Starting Page	995
Ending Page	999
File Size	1987318
Page Count	5
File Format	PDF
ISBN	9780769534978
DOI	10.1109/IITA.2008.122
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Wavelet transforms Programmable control PSNR Anisotropic magnetoresistance Noise reduction Filter bank Adaptive control Information technology Image denoising Noise level
Content Type	Text
Resource Type	Article

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