Fast Two-Phase Image Deblurring Under Impulse Noise

Authors:
Jian-Feng Cai;Raymond H. Chan;Mila Nikolova
Affiliations:
Department of Mathematics, UCLA, Los Angeles, USA 90095;Department of Mathematics, The Chinese University of Hong Kong, Shatin, Hong Kong;Centre de Mathématiques et de Leurs Applications, ENS de Cachan, CNRS, PRES UniverSud, Cachan Cedex, France 94235
Venue:
Journal of Mathematical Imaging and Vision
Year:
2010

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Abstract

In this paper, we propose a two-phase approach to restore images corrupted by blur and impulse noise. In the first phase, we identify the outlier candidates--the pixels that are likely to be corrupted by impulse noise. We consider that the remaining data pixels are essentially free of outliers. Then in the second phase, the image is deblurred and denoised simultaneously by a variational method by using the essentially outlier-free data. The experiments show several dB's improvement in PSNR with respect to the typical variational methods.