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On Total Variation Denoising: A New Majorization-Minimization Algorithm and an Experimental Comparisonwith Wavalet Denoising.

, , , and . ICIP, page 2633-2636. IEEE, (2006)

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A Signal Processing Perspective on Hyperspectral Unmixing: Insights from Remote Sensing., , , , , , , and . IEEE Signal Process. Mag., 31 (1): 67-81 (2014)Hyperspectral unmixing algorithm via dependent component analysis., and . IGARSS, page 4033-4036. IEEE, (2007)Learning dependent sources using mixtures of Dirichlet: Applications on hyperspectral unmixing., and . WHISPERS, page 1-5. IEEE, (2009)Parallel implementation of vertex component analysis for hyperspectral endmember extraction., , , , and . IGARSS, page 4078-4081. IEEE, (2012)Linear Spectral Unmixing via Matrix Factorization: Identifiability Criteria for Sparse Abundances., and . IGARSS, page 6155-6158. IEEE, (2018)Performance measures for classification systems with rejection., , and . Pattern Recognit., (2017)Total Variation-Based Image Deconvolution: a Majorization-Minimization Approach., , and . ICASSP (2), page 861-864. IEEE, (2006)Exploiting spatial information in semi-supervised hyperspectral image segmentation., , and . WHISPERS, page 1-4. IEEE, (2010)Convex formulation for hyperspectral image classification with superpixels., , , , and . IGARSS, page 3294-3297. IEEE, (2016)Phase imaging via sparse coding in the complex domain based on high-order svd and nonlocal BM3D techniques., , and . ICIP, page 4587-4591. IEEE, (2014)