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Learning object filters for high resolution satellite images using genetic algorithms

conference contribution
posted on 2003-01-01, 00:00 authored by H Zheng, Saeid Nahavandi, L Pan
This paper introduces a novel methodology for texture object detection using genetic algorithms. The method employs a kind of high performance detection filter defined as 2D masks, which are derived using genetic algorithm operating. The population of filters iteratively evaluated according to a statistical performance index corresponding to object detection ability, and evolves into an optimal filter using the evolution principles of genetic search. Experimental results of texture object detection in high resolution satellite images are presented to illustrate the merit and feasibility of the proposed method.

History

Event

Third International Asia-Pacific Environmental Remote Sensing. Remote Sensing of the Atmosphere, Ocean, Environment, and Space, 2002

Volume

4898

Pagination

102 - 108

Publisher

SPIE

Location

Hangzhou, China

Start date

2002-10-23

End date

2002-10-27

ISSN

0277-786X

Publication classification

EN.1 Other conference paper

Editor/Contributor(s)

S Unger, S Mao, Y Yasuoka

Title of proceedings

Proceedings : Image Processing and Pattern Recognition in Remote Sensing

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