Research Article | OPEN ACCESS
Blind Image Restoration Based on Signal-to-Noise Ratio and Gaussian Point Spread Function Estimation
Fengqing Qin
Department of Computer and Information Engineering, Yibin University, Yibin, 644007, P.R. China
Research Journal of Applied Sciences, Engineering and Technology 2013 4:1149-1153
Received: June 13, 2012 | Accepted: August 17, 2012 | Published: February 01, 2013
Abstract
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.
Keywords:
Blind image restoration, point spread function, signal-to-noise ration, wiener filtering,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
|
|
|
ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
|
Information |
|
|
|
Sales & Services |
|
|
|