DocumentCode :
3364410
Title :
Blind image restoration based on automatic blur identify and total variation minimization
Author :
Su, Xiuqin ; Li, Xiang ; Ji, Lei
Author_Institution :
Key Lab. of Ultrafast Photoelectric Diagnostics Technol., Xi´´an Inst. of Opt. & Precision Mech., Xi´´an, China
fYear :
2010
fDate :
26-28 June 2010
Firstpage :
2943
Lastpage :
2946
Abstract :
In this paper, an adaptive blind image restoration algorithm is proposed. According to the feature that the certain blur may lead to the specific component distortion in the cepstral domain, we develop an automatic algorithm using Fourier-Mellin transform to classify and identify the point spread function (PSF) with cepstrum: for the usual types of blur, such as linear motion blur and defocus blur, we restore it with Wiener filter; while for others, we propose an improved total variation (TV) blind restoration algorithm. The algorithm combines the typical methods and blind methods of image restoration, achieving the adaptive blind image restoration. Experimental results show that it is effective in restoring degraded images under different environments, and it improves the restoring performance significantly under the presence of high noise level.
Keywords :
Fourier transforms; Wiener filters; image motion analysis; image registration; image restoration; minimisation; Fourier-Mellin transform; Wiener filter; automatic blur identification; blind image restoration; defocus blur; linear motion blur; point spread function; total variation; total variation minimization; Cepstrum; Degradation; Fourier transforms; Image recognition; Image restoration; Inverse problems; Optical distortion; Parameter estimation; TV; Wiener filter; Fourier-Mellin transform; automatic blur identification; blind image restoration; cepstrum; total variation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechanic Automation and Control Engineering (MACE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7737-1
Type :
conf
DOI :
10.1109/MACE.2010.5536517
Filename :
5536517
Link To Document :
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