A MULTILEVEL ALGORITHM FOR SIMULTANEOUSLY DENOISING AND DEBLURRING IMAGES
Publication in refereed journal

香港中文大學研究人員

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摘要In this paper, we develop a fast multilevel algorithm for simultaneously denoising and deblurring images under the total variation regularization. Although much effort has been devoted to developing fast algorithms for the numerical solution and the denoising problem was satisfactorily solved, fast algorithms for the combined denoising and deblurring model remain to be a challenge. Recently several successful studies of approximating this model and subsequently finding fast algorithms were conducted which have partially solved this problem. The aim of this paper is to generalize a fast multilevel denoising method to solving the minimization model for simultaneously denoising and deblurring. Our new idea is to overcome the complexity issue by a detailed study of the structured matrices that are associated with the blurring operator. A fast algorithm can then be obtained for directly solving the variational model. Supporting numerical experiments on gray scale images are presented.
著者Chan RH, Chen K
期刊名稱SIAM Journal on Scientific Computing
出版年份2010
月份1
日期1
卷號32
期次2
出版社SIAM PUBLICATIONS
頁次1043 - 1063
國際標準期刊號1064-8275
電子國際標準期刊號1095-7197
語言英式英語
關鍵詞denoising and deblurring; image restoration; multilevel methods; regularization; total variation
Web of Science 學科類別Mathematics; Mathematics, Applied; MATHEMATICS, APPLIED

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