A Formal Γ-Convergence Approach for the Detection of Points in 2-D Images

被引：7

作者：

Graziani, Daniele ^{[1
]}

Blanc-Feraud, Laure ^{[1
]}

Aubert, Gilles ^{[2
]}

机构：

[1] Inria, CNRS INRIA UNSA Sophia Antipolis, ARIANA Project, F-06902 Sophia Antipolis, France

[2] Univ Nice Sophia Antipolis, Lab JA Dieudonne, F-06108 Nice 2, France

来源：

SIAM JOURNAL ON IMAGING SCIENCES | 2010年 / 3卷 / 03期

关键词：

points detection; curvature-dependent functionals; divergence-measure fields; Gamma-convergence; biological; 2-D images; APPROXIMATION;

D O I：

10.1137/080741604

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We propose a new variational model to locate points in 2-dimensional biological images. To this purpose we introduce a suitable functional whose minimizers are given by the points we want to detect. In order to provide numerical experiments we replace this energy with a sequence of more treatable functionals by means of the notion of Gamma-convergence.

引用

页码：578 / 594

页数：17

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