Data fusion applications:: Classification & mapping

被引：0

作者：

Fabre, S ^{[1
]}

Dhérété, P ^{[1
]}

机构：

[1] THALES Informat Syst, Toulouse, France

来源：

IGARSS 2003: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS I - VII, PROCEEDINGS: LEARNING FROM EARTH'S SHAPES AND SIZES | 2003年

关键词：

supervised classification; fusion; fuzzy logic; snakes; dynamic programming; matching;

D O I：

暂无

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

The non probabilistic theories have proved in the last years their ability to solve a large range of problems concerning imprecision. More recently, techniques using the Dempster-Shafer's and fuzzy set theories tried to deal with the problem related to the management of the uncertainty, the imprecision and the data fusion. The main difficulty of these methods concerns the knowledge, modeling. We present two fusion applications: classification and mapping using both Dempster-Shafer's and fuzzy set theories in order to combine heterogeneous information. These techniques are proposed to improve multi-spectral classification, GIS updating and mosaic building.

引用

页码：1053 / 1055

页数：3

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