An empirical identification method of Gaussian blur parameter for image deblurring

Authors:
Fen Chen;Jianglin Ma
Affiliations:
College of Automation, University of Electronic Science and Technology of China, Chengdu, China;Department of Geography, Faculty of Sciences, Vrije Universiteit Brussel, Brussel, Belgium
Venue:
IEEE Transactions on Signal Processing
Year:
2009

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Abstract

In this paper, we propose an empirical identification method of the Gaussian blur parameter for image deblurring. The parameter estimate is chosen from a collection of candidate parameters. The blurred image is restored by these candidate parameters under the assumption that the candidate is equal to the true value. The estimate is selected to be at the maximum point of the differential coefficients of restored image Laplacian L1 norm curve. Experimental results are presented to demonstrate the performance of the proposed method.