Classification of remote sensing images from urban areas using a fuzzy model

被引：0

作者：

Chanussot, J ^{[1
]}

Benediktsson, JA ^{[1
]}

Vincent, M ^{[1
]}

机构：

[1] LIS, INPG, Signals & Images Lab, F-38402 St Martin Dheres, France

来源：

IGARSS 2004: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM PROCEEDINGS, VOLS 1-7: SCIENCE FOR SOCIETY: EXPLORING AND MANAGING A CHANGING PLANET | 2004年

关键词：

possibility distribution; fuzzy sets; classification; mathematical morphology;

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 problem of classification of high-resolution remotely sensed images from urban areas is addressed. Previous studies have shown the interest of exploiting the local geometrical information of each pixel to improve the classification. This is performed using the derivative morphological profile (DMP) obtained with it granulometric approach, using respectively opening and closing operators. For each pixel, this DMP constitutes the feature vector on which the classification is based. In this paper, this vector is considered as a fuzzy measurement of the size of the structure. Compared with some possibility distributions, a membership degree is computed for each class. The decision is taken by selecting the class with the highest membership degree.

引用

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页码：556 / 559

页数：4

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