DocumentCode :
2313602
Title :
Color Image Restoration Based on Split Bregman Iteration Algorithm
Author :
Liya, Yi ; Xiaolei, Lu ; FuRong, Wang
Author_Institution :
Dept. of Electron. & Inf. Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
fYear :
2010
fDate :
9-11 Feb. 2010
Firstpage :
184
Lastpage :
187
Abstract :
In this paper, we modify the Split Bregman algorithm for color image restoration with the edge-preserving color image total variation model. The observed blurred images are assumed to be degraded by within channel and cross channel blurs. Our proposed algorithm is based on the Split Bregman process and simply requires Fast Fourier Transform in each iteration. Experimental comparisons using various types of blurs are reported, and the results show that, the proposed method significantly outperforms existing methods, such as the variable splitting alternative minimization algorithm and that adopted by MATLAB deblurring function, in terms of both objective signal to noise ratio and subjective vision quality. This demonstrates the efficiency of our proposed algorithms.
Keywords :
fast Fourier transforms; image colour analysis; image restoration; blurred images; color image restoration; edge-preserving color image total variation model; fast Fourier transform; split Bregman iteration algorithm; split Bregman process; Color; Degradation; Fast Fourier transforms; Gray-scale; Image restoration; Layout; Machine learning; Machine learning algorithms; Mathematical model; TV; cross channel; image restoration; split Bregman iteration; total variation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Computing (ICMLC), 2010 Second International Conference on
Conference_Location :
Bangalore
Print_ISBN :
978-1-4244-6006-9
Electronic_ISBN :
978-1-4244-6007-6
Type :
conf
DOI :
10.1109/ICMLC.2010.22
Filename :
5460745
Link To Document :
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