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2010
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Morphological wavelet transform with adaptive dyadic structures

11 years 2 months ago
Morphological wavelet transform with adaptive dyadic structures
We propose a two component method for denoising multidimensional signals, e.g. images. The first component uses a dynamic programing algorithm of complexity O(N log N) to find an optimal dyadic tree representation of a given multidimensional signal of N samples. The second component takes a signal with given dyadic tree representation and formulates the denoising problem for this signal as a Second Order Cone Program of size O(N). To solve the overall denoising problem, we apply these two algorithms iteratively to search for a jointly optimal denoised signal and dyadic tree representation. Experiments on images confirm that the approach yields denoised signals with improved PSNR and edge preservation.
Zhen James Xiang, Peter J. Ramadge
Added 03 Mar 2011
Updated 03 Mar 2011
Type Journal
Year 2010
Where ICIP
Authors Zhen James Xiang, Peter J. Ramadge
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