激光技术2017，Vol.41Issue(1)：106-112,7.DOI:10.7510/jgjs.issn.1001-3806.2017.01.022
一种改进的基于自动形态学的端元提取算法
An improved endmember extraction algorithm based on automated morphology
摘要
Abstract
Morphological operators used in the automated morphological endmember extraction (AMEE) algorithm didn' t acquire correct result in the area of pure pixel concentration distribution. The dilation operation only chose one candidate endmember from each structure element and would lose some important pixels. In order to solve the problem, the AMEE algorithm was modified by an improved morphological operator and new structural element. The improved morphological operator was proposed after introducing the concept of reference spectral vector, and a new calculation method of morphological eccentricity index was given. To avoid information loss, four candidate endmembers were chosen from each improved even-numbered structure element. The modified automated morphological endmember extraction algorithm was tested based on a hyperspectral data set. The experimental results show that the improved method can obtain correct candidate endmembers from the area of pure pixel concentration distribution, and information loss in the procedure of dilation is also avoided. The proposed method produces more accurate results of endmember extraction and the spectral unmixing.关键词
遥感/高光谱图像/端元提取/形态学Key words
remote sensing/hyperspectral image/endmember extraction/morphology分类
天文与地球科学引用本文复制引用
方俊龙,郭宝峰,沈宏海,杨名宇..一种改进的基于自动形态学的端元提取算法[J].激光技术,2017,41(1):106-112,7.基金项目
国家自然科学基金资助项目(61375011) （61375011）
浙江省自然科学基金资助项目(LY13F030015) （LY13F030015）
