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http://dx.doi.org/10.13067/JKIECS.2016.11.1.45

Self-Regularization Method for Image Restoration  

Yoo, Jae-Hung (Dept. of Computer Engineering, Chonnam Nat. Univ.)
Publication Information
The Journal of the Korea institute of electronic communication sciences / v.11, no.1, 2016 , pp. 45-52 More about this Journal
Abstract
This paper suggests a new method of finding regularization parameter for image restoration problems. Wiener filter requires priori information such that power spectrums of original image and noise. Constrained least squares restoration also requires knowledge of the noise level. If the prior information is not available, separate optimization functions for Tikhonov regularization parameter are suggested in the literature such as generalized cross validation and L-curve criterion. In this paper, self-regularization method that connects bias term of augmented linear system and smoothing term of Tikhonov regularization is introduced in the frequency domain and applied to the image restoration problems. Experimental results show the effectiveness of the proposed method.
Keywords
Self-Regularization; LMS rule; Tikhonov Regularization; Image Restoration;
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Times Cited By KSCI : 4  (Citation Analysis)
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