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	A new method for parameter estimation of edge-preserving regularization in image restoration
	Gu, Xiaojuan ; Gao, Li
	2009
关键词	Gaussian noise Image restoration Edge-preserving regularization Parameter estimation Constrained optimization problem VARIATIONAL APPROACH NOISE MINIMIZATION ALGORITHMS SELECTION
英文摘要	In image restoration, the so-called edge-preserving regularization method is used to solve an optimization problem whose objective function has a data fidelity term and a regularization term, the two terms are balanced by a parameter lambda. In some aspect, the value of lambda determines the quality of images. In this paper, we establish a new model to estimate the parameter and propose an algorithm to solve the problem. In order to improve the quality of images, in our algorithm, an image is divided into some blocks. On each block, a corresponding value of lambda has to be determined. Numerical experiments are reported which show efficiency of our method. (c) 2008 Elsevier B.V. All rights reserved.; Mathematics, Applied; SCI(E); EI; 6; ARTICLE; 2; 478-486; 225
语种	英语
出处	EI ; SCI
出版者	计算与应用数学杂志
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/157730]
专题	数学科学学院
推荐引用方式 GB/T 7714	Gu, Xiaojuan,Gao, Li. A new method for parameter estimation of edge-preserving regularization in image restoration. 2009-01-01.

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