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VLSM
2005
Springer

Color Image Deblurring with Impulsive Noise

10 years 3 months ago
Color Image Deblurring with Impulsive Noise
Abstract. We propose a variational approach for deblurring and impulsive noise removal in multi-channel images. A robust data fidelity measure and edge preserving regularization are employed. We consider several regularization approaches, such as Beltrami flow, Mumford-Shah and Total-Variation Mumford-Shah. The latter two methods are extended to multi-channel images and reformulated using the Γ-convergence approximation. Our main contribution is in the unification of image deblurring and impulse noise removal in a multi-channel variational framework. Theoretical and experimental results show that the Mumford-Shah and Total Variation Mumford Shah regularization methods are superior to other color image restoration regularizers. In addition, these two methods yield a denoised edge map of the image.
Leah Bar, Alexander Brook, Nir A. Sochen, Nahum Ki
Added 28 Jun 2010
Updated 28 Jun 2010
Type Conference
Year 2005
Where VLSM
Authors Leah Bar, Alexander Brook, Nir A. Sochen, Nahum Kiryati
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