DocumentCode :
2307035
Title :
A Blind Image Restoration Method Based on PSF Estimation
Author :
Qin, Feng-Qing ; Min, Jun ; Guo, Hong-Rong
Author_Institution :
Dept. of Comput. Sci. & Technol., Yibin Univ., Yibin, China
Volume :
2
fYear :
2009
fDate :
19-21 May 2009
Firstpage :
173
Lastpage :
176
Abstract :
In order to improve the quality of the restored image, a blind image restoration method is proposed, by estimating the blur function of the imaging model. Firstly, the parameters of the Gaussian point spread function (PSF) of the observed image are estimated. Through Wiener filter image restoration algorithm, multiple error-parameter curves are generated at different parameters. According to these curves, the size and standard deviation of PSF may be estimated. Then, utilizing the estimated PSF, the blurred image is restored through Wiener filter. Experimental results show that this PSF estimation method can estimate the parameters of Gaussian PSF accurately, and justify the fact that PSF estimation plays an important part in image restoration. The PSNR of the restored image has the highest PSNR around the real PSF, and the PSNR decreases when the estimated PSF is far away from its real value.
Keywords :
Gaussian distribution; Wiener filters; image restoration; optical transfer function; parameter estimation; Gaussian point spread function; PSF estimation method; Wiener filter; blind image restoration method; blur function estimation; error-parameter curves; Computer science; Convolution; Discrete Fourier transforms; Image reconstruction; Image restoration; Optical imaging; PSNR; Signal to noise ratio; Software engineering; Wiener filter; Blind; Image Restoration; Point spread function; Wiener filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering, 2009. WCSE '09. WRI World Congress on
Conference_Location :
Xiamen
Print_ISBN :
978-0-7695-3570-8
Type :
conf
DOI :
10.1109/WCSE.2009.95
Filename :
5319688
Link To Document :
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