Classification of MODIS images based on band combination

Yan Li; Ruifang Zhai; Ying Wang

doi:10.1117/12.539833

25 September 2003 Classification of MODIS images based on band combination

Yan Li, Ruifang Zhai, Ying Wang

Proceedings Volume 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition; (2003) https://doi.org/10.1117/12.539833
Event: Third International Symposium on Multispectral Image Processing and Pattern Recognition, 2003, Beijing, China

Abstract

This paper discusses the existing three optimal band combination rules of hyperspectral remote sensing images. They are joint entropy, optimal index factor and Sheffield index respectively. Three bands of MODIS images data are combined arbitrarily according to the three rules, so the best three bands combination images of the three rules are acquired. On the basis of this, the three images are all classified in term of maximum likelihood classifier. Also, the influence of each band combination to the classification performance is discussed. The experiment result proves that the best classification performance of the MODIS images based on the three bands combination is the combination image based on optimal index factor.

Citation Download Citation

Yan Li, Ruifang Zhai, and Ying Wang "Classification of MODIS images based on band combination", Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); https://doi.org/10.1117/12.539833

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