Deblurring of Color Images Corrupted by Impulsive Noise

Author

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

Author_Institution

Dept. of Electr. & Comput. Eng., Minnesota Univ.

Volume

16

Issue

4

fYear

2007

fDate

4/1/2007 12:00:00 AM

Firstpage

1101

Lastpage

1111

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

Keywords

approximation theory; edge detection; image colour analysis; image denoising; image restoration; Mumford-Shah functional; blur noise; color edge detection; color images deblurring; image deblurring; image denoising; impulsive noise; multichannel image restoration; Color; Colored noise; Deconvolution; Gaussian noise; Image denoising; Image processing; Image restoration; Mathematics; Noise level; Noise reduction; Color image processing; Mumford–Shah (MS) functional; deblurring; denoising; impulse noise; Algorithms; Artifacts; Artificial Intelligence; Color; Colorimetry; Image Enhancement; Image Interpretation, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/TIP.2007.891805

Filename

4130413