Mumford-Shah functionals on graphs and their asymptotics

被引:10
|
作者
Caroccia, Marco [1 ]
Chambolle, Antonin [2 ]
Slepcev, Dejan [3 ]
机构
[1] Univ Roma Tor Vergata, Dipartimento Matemat, I-00133 Rome, Italy
[2] Ecole Polytech, CMAP, F-91128 Palaiseau, France
[3] Carnegie Mellon Univ, Dept Math Sci, Pittsburgh, PA 15213 USA
基金
美国安德鲁·梅隆基金会;
关键词
nonlocal variational problems; variational problems with randomness; discrete to continuum limit; asymptotic consistency; Gamma convergence; regression; FINITE-DIFFERENCE APPROXIMATION; CONSISTENCY; RECOVERY;
D O I
10.1088/1361-6544/ab81ee
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
We consider adaptations of the Mumford-Shah functional to graphs. These are based on discretizations of nonlocal approximations to the Mumford-Shah functional. Motivated by applications in machine learning we study the random geometric graphs associated to random samples of a measure. We establish the conditions on the graph constructions under which the minimizers of graph Mumford-Shah functionals converge to a minimizer of a continuum Mumford-Shah functional. Furthermore we explicitly identify the limiting functional. Moreover we describe an efficient algorithm for computing the approximate minimizers of the graph Mumford-Shah functional.
引用
收藏
页码:3846 / 3888
页数:43
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