Deblurring of color images corrupted by impulsive noise

Leah Bar*, Alexander Brook, Nir Sochen, Nahum Kiryati

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

95 Scopus citations


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 Γ-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.

Original languageEnglish
Pages (from-to)1101-1111
Number of pages11
JournalIEEE Transactions on Image Processing
Issue number4
StatePublished - Apr 2007


FundersFunder number
A.M.N. Foundation
EC 6th Framework IST Programme
Israel Science Foundation


    • Color image processing
    • Deblurring
    • Denoising
    • Impulse noise
    • Mumford-Shah (MS) functional


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