Large-scale integer programs in image analysis
成果类型：
Article
署名作者：
Dahl, G; Storvik, G; Fadnes, A
署名单位：
University of Oslo; University of Oslo
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.50.3.490.7741
发表日期：
2002
页码：
490-500
关键词：
摘要：
An important problem in image analysis is to segment an image into regions with different class labels. This is relevant in applications in medicine and cartography. In a proper statistical framework this problem may be viewed as a discrete optimization problem. We present two integer linear programming formulations of the problem and study some properties of these models and associated polytopes. Different algorithms for solving these problems are suggested and compared on some realistic data. In particular, a Lagrangian algorithm is shown to have a very promising performance. The algorithm is based on the technique of cost splitting and uses the fact that certain relaxed problems may be solved as shortest path problems.