Noisy Image Decomposition Based On Texture Detecting Function
Author(s) -
Ruihua Liu,
Ruizhi Jia,
Liyun Su
Publication year - 2012
Publication title -
international journal of image graphics and signal processing
Language(s) - English
Resource type - Journals
eISSN - 2074-9082
pISSN - 2074-9074
DOI - 10.5815/ijigsp.2012.03.03
Subject(s) - decomposition , image (mathematics) , computer science , artificial intelligence , function (biology) , texture (cosmology) , gaussian , computer vision , image texture , ideal (ethics) , resolution (logic) , pattern recognition (psychology) , property (philosophy) , dual (grammatical number) , algorithm , mathematics , image processing , physics , evolutionary biology , biology , art , ecology , philosophy , literature , epistemology , quantum mechanics
At present, most of image decomposition models only apply to some ideal images, such as, noisefree, without blurring and super resolution images, and so on. In this paper, they propose a novel decomposition model based on dual method and texture detecting function for noisy image. Firstly, they prove the existence of minimal solutions of the noisy decomposition model functional. Secondly, they write down an alterative implementation algorithm. Finally, they give some numerical experiments, which show that their model can effectively work for Gaussian noisy image decomposition.
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