A New Interscale and Intrascale Orthonormal Wavelet Thresholding for SURE-Based Image Denoising

The interscale Stein's unbiased risk estimator (SURE)-based approach introduced by Luisier is a recent state of the art in orthonormal wavelet denoising, but it is not very effective for those images that have substantial high-frequency contents. To solve this problem, we introduce an effective...

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Bibliographic Details
Published in:IEEE signal processing letters 2008, Vol.15, p.139-142
Main Authors: Fengxia Yan, Fengxia Yan, Lizhi Cheng, Lizhi Cheng, Silong Peng, Silong Peng
Format: Article
Language:English
Subjects:
Adaptive algorithm
Computer vision
Image denoising
Image processing
intrascale and interscale dependencies
Noise reduction
Propagation delay
Signal processing algorithms
State estimation
Stein's unbiased risk estimator (SURE) minimization
Wavelet coefficients
Wavelet transforms
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Summary:The interscale Stein's unbiased risk estimator (SURE)-based approach introduced by Luisier is a recent state of the art in orthonormal wavelet denoising, but it is not very effective for those images that have substantial high-frequency contents. To solve this problem, we introduce an effective integration of the intrascale correlations within the interscale SURE-based approach. We show that the consideration of both the intrascale and interscale dependencies of wavelet coefficients brings more denoising gains than those obtained with the interscale SURE-based approach, especially for denoising of images that have substantial textures such as the Barbara image.
ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2007.914790