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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/1237

Title: Particle Swarm Optimization Based Regularization for Image Restoration
Authors: Dash, R
Majhi, B
Keywords: Degraded images;
Direct inversion;
Frequency domains;
Ill posed;
Image restoration;
Inversion process;
Regularization parameters;
Regularization technique;
Restoration process;
Standing problems
Issue Date: 2009
Publisher: IEEE
Citation: 2009 World Congress on Nature and Biologically Inspired Computing, NABIC 2009; Coimbatore; 9 December 2009 through 11 December 2009; Category number CFP0995H; Code 79534; Article number 5393754, Pages 1253-1257
Abstract: Image restoration from a degraded observation has been a long standing problem in image processing. It requires a direct inversion of the degradation function in frequency domain which is ill posed in nature. So regularization has been used in the restoration process. The selection of regularization parameter still remains a difficult problem due to the amplification of noise in the inversion process. In this paper, we have proposed a PSO based regularization technique which adapts the regularization parameters depending on the noise and blurring conditions in the degraded image. Experimental results are presented to validate the efficiency of the proposed scheme.
URI: http://dx.doi.org/10.1109/NABIC.2009.5393754
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