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Vol. 167, Issue 3, March 2014, pp. 36-42




Based on Total Variation Regularization Iterative Blind Image Restoration Algorithm

1 Keyong Shao, 1 Yun Zou, 1 Yuanhong Liu, 1 Cheng Li, 2 Bosi Fu

1 Da Qing, Northeast Petroleum University, 163318, China
2 Da Qing, Two oil production company, 163000, China
1 Tel.: 13904867536

E-mail: 370345267@qq.com


Received: 20 December 2013 /Accepted: 28 February 2014 /Published: 31 March 2014

Digital Sensors and Sensor Sysstems


Abstract: In the process of image formation, transmission and recording, because of the imaging system, transmission medium and the equipment is not perfect, it makes the quality of image declined, the key of blurred image restoration is to estimate the Point Spread Function. Because Point Spread Function canít be obtained, we canít get the precise of fuzzy model. In this paper, we study a kind of blind image restoration method, the total variation regularization and iterative blind deconvolution is combined, we use Total Variation regularization algorithm in fuzzy identification stage, and use the combined of Total Variation regularization and iterative blind deconvolution algorithm in image restoration stage. In order to obtain the only solution of the algorithm, we also use the image and Point Spread Function constraints in the iterative process. The simulation results show that the proposed algorithm is more effective than some of the existing algorithms.


Keywords: Total variation (TV) regularization, Iterative, Blind deconvolution, Point spread function (PSF), Image restoration.


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