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Proceedings Paper

GA-hyperplane segmentation method for MODIS data
Author(s): Qiqing Li; Jianwen Ma; Hasi Bagan
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Paper Abstract

For the traditional method of hyper-plane segmentation, the location of hyper-plane in data space was given by statistical method. In the case of the statistical value of regions is smaller than in the region, the statistical method was not effective. The character of genetic algorithm is global searching optimally. Taken this mathematical advantage the location of Hyper-plane could be located easily. In this paper, EOS/MODIS imagery data is used to test this method. The result is proved that Genetic Algorithms-Hyper-plane is better than MLC method by using same training data.

Paper Details

Date Published: 25 September 2003
PDF: 4 pages
Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); doi: 10.1117/12.538713
Show Author Affiliations
Qiqing Li, Institute of Remote Sensing Applications, CAS (China)
Jianwen Ma, Institute of Remote Sensing Applications, CAS (China)
Hasi Bagan, Institute of Remote Sensing Applications (China)


Published in SPIE Proceedings Vol. 5286:
Third International Symposium on Multispectral Image Processing and Pattern Recognition
Hanqing Lu; Tianxu Zhang, Editor(s)

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