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Proximal algorithms for multicomponent image recovery problems

Abstract : In recent years, proximal splitting algorithms have been applied to various monocomponent signal and image recovery problems. In this paper, we address the case of multicomponent problems. We first provide closed form expressions for several important multicomponent proximity operators and then derive extensions of existing proximal algorithms to the multicomponent setting. These results are applied to stereoscopic image recovery, multispectral image denoising, and image decomposition into texture and geometry components.
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Submitted on : Tuesday, May 28, 2013 - 1:05:11 PM
Last modification on : Thursday, May 12, 2022 - 8:38:02 AM
Long-term archiving on: : Tuesday, September 3, 2013 - 9:51:12 AM


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Luis M. Briceno-Arias, Patrick Louis Combettes, Jean-Christophe Pesquet, Nelly Pustelnik. Proximal algorithms for multicomponent image recovery problems. Journal of Mathematical Imaging and Vision, Springer Verlag, 2011, 41 (1-2), pp.3-22. ⟨10.1007/s10851-010-0243-1⟩. ⟨hal-00826810⟩



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