Variational deconvolution of multi-channel images with inequality constraints \

被引:0
|
作者
Welk, Martin [1 ]
Nagy, James G. [2 ]
机构
[1] Univ Saarland, Fac Math & Comp Sci, Math Image Anal Grp, Bldg E11, D-66041 Saarbrucken, Germany
[2] Emory Univ, Dept Math & Comp Sci, Atlanta, GA 30322 USA
基金
美国国家科学基金会;
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A constrained variational deconvolution approach for multi-channel images is presented. Constraints are enforced through a reparametrisation which allows a differential geometric reinterpretation. This view point is used to show that the deconvolution problem can be formulated as a standard gradient descent problem with an underlying metric that depends on the imposed constraints. Examples are given for bound constrained colour image deblurring, and for diffusion tensor magnetic resonance imaging with positive definiteness constraint. Numerical results illustrate the effectiveness of the methods.
引用
收藏
页码:386 / +
页数:2
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