Variational approach for edge-preserving regularization using coupled PDE's

被引:151
作者
Teboul, S [1 ]
Blanc-Feraud, L
Aubert, G
Barlaud, M
机构
[1] Lab Informat Signaux & Syst Sophia Antipolis, F-06560 Valbonne, France
[2] Univ Nice, CNRS, URA 168, F-06108 Nice 2, France
关键词
anisotropic diffusion; edge-preserving regularization; Mumford-Shah functional; segmentation; systems of coupled PDE's; variational approach;
D O I
10.1109/83.661189
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper deals with edge-preserving regularization for inverse problems in image processing, We first present a synthesis of the main results we have obtained in edge-preserving regularization by using a variational approach, We recall the model involving regularizing functions phi and we analyze the geometry-driven diffusion process of this model in the three-dimensional (3-D) case, Then half-quadratic theorem is used to give a very simple reconstruction algorithm, After a critical analysis of this model, we propose another functional to minimize for the edge-preserving reconstruction purpose, It results in solving two coupled partial differential equations (PDE's): one processes the intensity, the other the edges, We study the relationship with similar PDE systems in particular with the functional proposed by Ambrosio-Tortorelli [1], [2] in order to approach the Mumford-Shah functional [3] developed in the segmentation application, Experimental results on synthetic and real images are presented.
引用
收藏
页码:387 / 397
页数:11
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