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
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