GA-hyperplane segmentation method for MODIS data

Qiqing Li; Jianwen Ma; Hasi Bagan

doi:10.1117/12.538713

25 September 2003 GA-hyperplane segmentation method for MODIS data

Qiqing Li, Jianwen Ma, Hasi Bagan

Proceedings Volume 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition; (2003) https://doi.org/10.1117/12.538713
Event: Third International Symposium on Multispectral Image Processing and Pattern Recognition, 2003, Beijing, China

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.

Citation Download Citation

Qiqing Li, Jianwen Ma, and Hasi Bagan "GA-hyperplane segmentation method for MODIS data", Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); https://doi.org/10.1117/12.538713

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