光电子快报(英文版), 2014, 10 (5): 387, Published Online: Oct. 12, 2017  

A hyperspectral image endmember extraction algorithm based on generalized morphology

Author Affiliations
1 College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
2 Electric and Control Engineering College, Heilongjiang University of Science and Technology, Harbin 150022, China
Abstract
Generalized morphological operator can generate less statistical bias in the output than classical morphological operator. Comprehensive utilization of spectral and spatial information of pixels, an endmember extraction algorithm based on generalized morphology is proposed. For the limitations of morphological operator in the pixel arrangement rule and replacement criteria, the reference pixel is introduced. In order to avoid the cross substitution phenomenon at the boundary of different object categories in the image, an endmember is extracted by calculating the generalized opening- closing (GOC) operator which uses the modified energy function as a distance measure. The algorithm is verified by using simulated data and real data. Experimental results show that the proposed algorithm can extract endmember automatically without prior knowledge and achieve relatively high extraction accuracy.

WANG Dong-hui, YANG Xiu-kun, ZHAO Yan. A hyperspectral image endmember extraction algorithm based on generalized morphology[J]. 光电子快报(英文版), 2014, 10(5): 387.

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