A High-Order Scheme for Image Segmentation via a Modified Level-Set Method

被引:12
|
作者
Falcone, Maurizio [1 ]
Paolucci, Giulio [1 ]
Tozza, Silvia [2 ]
机构
[1] Sapienza Univ Roma, Dipartimento Matemat, I-00185 Rome, Italy
[2] Sapienza Univ Roma, UO Dipartimento Matemat, Ist Nazl Alta Matemat, I-00185 Rome, Italy
来源
SIAM JOURNAL ON IMAGING SCIENCES | 2020年 / 13卷 / 01期
关键词
image segmentation; level-set method; Hamilton-Jacobi equations; filtered scheme; smoothness indicators; ESSENTIALLY NONOSCILLATORY SCHEMES; FILTERED SCHEMES; ACTIVE CONTOURS; CURVATURE; ENO; MODEL;
D O I
10.1137/18M1231432
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we propose a high-order accurate scheme for image segmentation based on the level-set method. In this approach, the curve evolution is described as the 0-level set of a representation function, but we modify the velocity that drives the curve to the boundary of the object in order to obtain a new velocity with additional properties that are extremely useful to develop a more stable high-order approximation with a small additional cost. The approximation scheme proposed here is the first 2D version of an adaptive "filtered" scheme recently introduced and analyzed by the authors in one dimension. This approach is interesting since the implementation of the filtered scheme is rather efficient and easy. The scheme combines two building blocks (a monotone scheme and a high-order scheme) via a filter function and smoothness indicators that allow one to detect the regularity of the approximate solution adapting the scheme in an automatic way. Some numerical tests on synthetic and real images confirm the accuracy of the proposed method and the advantages given by the new velocity.
引用
收藏
页码:497 / 534
页数:38
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