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Blind image restoration based on Wiener filtering and defocus point spread function estimation

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1 Author(s)
Fengqing Qin ; School of Computer and Information Engineering, Yibin University, 644007, China

In order to improve the quality of the defocus blurred image, the defocus point spread function (PSF) of the imaging system needs to be estimated. A blind image restoration algorithm was proposed, in which the defocus PSF of the blurred image was estimated through error-parameter estimation method. Firstly, the error-parameter curve was generated through Wiener filtering algorithm. Then, by analyzing the error-parameter curve, the defocus radius of the blurred image was estimated. Finally, utilizing the estimated PSF, image restoration was performed through Wiener filtering algorithm. Experimental results showed that the defocus PSF was estimated with high accuracy, and justified the fact that the defocus PSF estimation plays a great important part in blind image restoration.

Published in:

Image and Signal Processing (CISP), 2012 5th International Congress on

Date of Conference:

16-18 Oct. 2012