NDLI: Wavelet approaches to still image denoising

Content Provider	IEEE Xplore Digital Library
Author	Lu, W.-S.
Copyright Year	1998
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Victoria Univ., BC, Canada (Lu, W.-S.)
Abstract	This paper describes three wavelet-based methods for noise reduction of still images: (i) hyperbolic shrinkage with a level-dependent thresholding policy; (ii) hyperbolic shrinkage with a two-dimensional cross-validation-based thresholding; and (iii) block SVD-wavelet denoising. All three methods make use of hyperbolic shrinkage rather than conventional soft shrinkage. As the thresholding of wavelet coefficients is concerned, at each level of wavelet decomposition, the first method employs a level-dependent universal threshold determined by the coefficient variance and the number of the coefficients at that level; while the second method extends Nason's (1994) cross-validation approach to the 2-D case. In the third method, an image is divided into several subimages (blocks) and singular value decomposition (SVD) is applied to each block. The singular values obtained are then truncated and each pair of singular vectors are treated as 1-D noisy signals and are denoised using a wavelet-based method. The subimages are then reconstructed using the truncated singular values and denoised singular vectors.
Starting Page	1705
Ending Page	1709
File Size	726632
Page Count	5
File Format	PDF
ISBN	0818683163
ISSN	10586393
DOI	10.1109/ACSSC.1997.679193
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1997-11-02
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image denoising Noise reduction Discrete wavelet transforms Noise level Finite impulse response filter Gaussian noise Singular value decomposition Image reconstruction Wavelet coefficients Testing
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Signal Processing

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