期刊
PATTERN RECOGNITION
卷 36, 期 8, 页码 1747-1763出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/S0031-3203(02)00323-0
关键词
singular value decomposition (SVD); wavelet transform; image denoising; edge detection; adaptive filtering
Image denoising is an important issue in image preprocessing. Two popular methods to the problem are singular value decomposition (SVD) and wavelet transform. Various denoising algorithms based on these two methods have been independently developed. This paper proposes an approach for image denoising by performing SVD filtering in detail subbands of wavelet domain, where SVD filtering is adaptive to the inhomogeneous nature of natural images. Comparisons were made with respect to both SVD-based filtering methods and wavelet transform-based methods. (C) 2003 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
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