Efficient Image Segmentation and Restoration Using Parametric Curve Evolution with Junctions and Topology Changes

被引：17
|
作者：
Benninghoff, Heike [1 ]
Garcke, Harald [2 ]
机构：
[1] Deutsch Zentrum Luft & Raumfahrt DLR, D-82234 Wessling, Germany
[2] Univ Regensburg, Fak Math, D-93040 Regensburg, Germany
来源：
SIAM JOURNAL ON IMAGING SCIENCES | 2014年 / 7卷 / 03期
关键词：
image segmentation; restoration; active contours; region-based; Mumford-Shah; Chan-Vese; parametric method; variational methods; topology changes; equidistribution; triple junctions; ACTIVE CONTOURS; MUMFORD;
D O I：
10.1137/130932430
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Curve evolution schemes are introduced for image segmentation based on a region-based contour model allowing for junctions, vector-valued images, and topology changes. Together with an a posteriori denoising in the segmented homogeneous regions, this leads to a fast and efficient method for image segmentation and restoration. An uneven spread of mesh points is avoided by using the tangential degrees of freedom. Several numerical simulations on artificial test problems and on real images illustrate the performance of the method.
引用
收藏
页码：1451 / 1483
页数：33
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