two new efficient iterative regularization methods for image restoration problems

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ID: 159540
2013
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Abstract
Iterative regularization methods are efficient regularization tools for image restoration problems. The IDR(s) and LSMR methods are state-of-the-arts iterative methods for solving large linear systems. Recently, they have attracted considerable attention. Little is known of them as iterative regularization methods for image restoration. In this paper, we study the regularization properties of the IDR(s) and LSMR methods for image restoration problems. Comparative numerical experiments show that IDR(s) can give a satisfactory solution with much less computational cost in some situations than the classic method LSQR when the discrepancy principle is used as a stopping criterion. Compared to LSQR, LSMR usually produces a more accurate solution by using the L-curve method to choose the regularization parameter.
Reference Key
zhao2013abstracttwo Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Chao Zhao;Ting-Zhu Huang;Xi-Le Zhao;Liang-Jian Deng
Journal science and technology of advanced materials
Year 2013
DOI
10.1155/2013/129652
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