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Deblurring of color images corrupted by impulsive noise
Leah Bar1, Alexander Brook, Nir Sochen
1Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455, USA. barxx002@umn.edu
Abstract:
We consider the problem of restoring a multichannel image corrupted by blur and impulsive noise (e.g., salt-and-pepper noise). Using the variational framework, we consider the L1 fidelity term and several possible regularizers. In particular, we use generalizations of the Mumford-Shah (MS) functional to color images and gamma-convergence approximations to unify deblurring and denoising. Experimental comparisons show that the MS stabilizer yields better results with respect to Beltrami and total variation regularizers. Color edge detection is a beneficial by-product of our methods.
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