Adaptive singular value decomposition in wavelet domain for image denoising |
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Authors: | Zujun Hou Author Vitae |
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Affiliation: | Department of Computational Science, Faculty of Science, National University of Singapore, Singapore 117543, Singapore |
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Abstract: | 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. |
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Keywords: | Singular value decomposition (SVD) Wavelet transform Image denoising Edge detection Adaptive filtering |
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