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Abstract
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Article Information:
Blind Image Restoration Based on Signal-to-Noise Ratio and Gaussian Point Spread Function Estimation
Fengqing Qin
Corresponding Author: Fengqing Qin
Submitted: June 13, 2012
Accepted: August 17, 2012
Published: February 01, 2013 |
Abstract:
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In order to improve the quality of restored image, a blind image restoration algorithm is proposed, in which both the Signal-to-Noise Ratio (SNR) and the Gaussian Point Spread Function (PSF) of the degraded image are estimated. Firstly, the SNR of the degraded image is estimated through local deviation method. Secondly, the PSF of the degraded image is estimated through error-parameter method. Thirdly, Utilizing the estimated SNR and PSF, high resolution image is restored through Wiener filtering restoration algorithm. Experimental results show that the quality and peak signal-to-noise of the restored image are better around the real value and justify the fact that the SNR an-d PSF estimation plays great important part in blind image restoration.
Key words: Blind image restoration, point spread function, signal-to-noise ration, wiener filtering, , ,
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Abstract
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Cite this Reference:
Fengqing Qin, . Blind Image Restoration Based on Signal-to-Noise Ratio and Gaussian Point Spread Function Estimation. Research Journal of Applied Sciences, Engineering and Technology, (04): 1149-1153.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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