Clustering analysis as a basic tool for hyperspectral remote sensing image

Han Xu; Xiaojuan Li; Xiaowei Gao

doi:10.1117/12.902115

23 November 2011 Clustering analysis as a basic tool for hyperspectral remote sensing image

Han Xu, Xiaojuan Li, Xiaowei Gao

Proceedings Volume 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications; 800619 (2011) https://doi.org/10.1117/12.902115
Event: Seventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2011), 2011, Guilin, China

Abstract

Clustering analysis groups data objects based on information only found in the data that describes the objects and the relationships. As it is a spatial method, more research are focused on remote sensing application recently. This paper presents comparison of two classic cluster algorithms used in hyperspectral remote sensing image classification and the results showed that the classification of maximum likelihood algorithm is better than ISODATA algorithm.

Citation Download Citation

Han Xu, Xiaojuan Li, and Xiaowei Gao "Clustering analysis as a basic tool for hyperspectral remote sensing image", Proc. SPIE 8006, MIPPR 2011: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 800619 (23 November 2011); https://doi.org/10.1117/12.902115

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