A hyperspectral image endmember extraction algorithm based on generalized morphology  

作　　者：王东辉 杨秀坤 赵岩 

机构地区：[1]College of Information and Communication Engineering,Harbin Engineering University [2]Electric and Control Engineering College,Heilongjiang University of Science and Technology

出　　处：《Optoelectronics Letters》2014年第5期387-390,共4页光电子快报（英文版）

基　　金：supported by the National Natural Science Foundation of China(No.61275010);the PhD Programs Foundation of Ministry of Education of China(No.20132304110007)

摘　　要：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.

关 键 词：EXTRACTION Morphology PIXELS Spectroscopy Comprehensive utilizations Endmember extraction algorithms Extraction accuracy Generalized morphological operators Hyper spectral images Morphological operator Object categories Spatial informations 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TP751.1[自动化与计算机技术—计算机科学与技术]