Image Restoration with Regularization Convex Optimization Approach
Publish place: Journal of Electrical Systems and Signals، Vol: 2، Issue: 2
Publish Year: 1393
Type: Journal paper
Language: English
View: 487
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Document National Code:
JR_JESS-2-2_005
Index date: 10 September 2017
Image Restoration with Regularization Convex Optimization Approach abstract
In this paper, Tikhonov regularization with l-curve parameter estimation as convex optimization problem has been proposed in image restoration as a solution of ill-posed problem stem from sparse and large scale blurring matrix which has many singular values of different orders of magnitude close to the origin. Also, since the restored image is so sensitive to initial guess (start point) of optimization algorithm, a new schema for feasible set and feasible start point has been proposed. Some numerical results show the efficiency of the proposed algorithm in comparison with previous proposed methods.
Image Restoration with Regularization Convex Optimization Approach Keywords:
Image Restoration with Regularization Convex Optimization Approach authors
Abdolreza Rashno
Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran.
Foroogh Sadat Tabataba
Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran
Saeed Sadri
Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, Iran