摘要
针对现有端元提取方法从数据光谱或空间或特征信息的单一方面出发进行混合像元分解、不同类型端元难以区分等不足,提出一种扩展形态学与正交子空间投影结合的端元自动提取方法.利用扩展膨胀和腐蚀操作,通过计算形态离心率指数进行高光谱数据的端元数据集计算;利用光谱角匹配方法提取不同类型的端元,通过向端元正交子空间投影消除已经提取端元的影响;并通过航空高光谱数据进行算法性能验证.实验结果表明:提出方法能够实现在无任何先验信息情况下图像端元的自动提取,并且能够有效地区分相似光谱端元.
An automatic endmember extraction method based on the extended morphology and the orthogonal subspace projection was proposed to solve the problems,including identification of different endmembers with similar spectra and the endmembers extraction used by the spectral or spatial information only.Extended dilation and erosion operators were used to calculate the morphological eccentricity index(MEI),and the MEI was used to extract the endmember set.Spectral angle matching(SAM) was applied to distinguish different endmembers,and then the endmember was projected to its orthogonal subspace to eliminate the effect of endmembers that had been extracted.The airborne hyperspectral data was used to evaluate the performance of this method.The results illuminate that image endmembers are extracted automatically without any prior information and endmembers with similar spectra are distinguished effectively.
出处
《北京航空航天大学学报》
EI
CAS
CSCD
北大核心
2010年第12期1457-1460,共4页
Journal of Beijing University of Aeronautics and Astronautics
基金
国家863计划资助项目(2008AA121102
2008AA12A201)
长江学者和创新团队发展计划资助项目(IRT0705)
关键词
高光谱遥感
端元提取
扩展形态学
正交子空间投影
hyperspectral remote sensing
endmember extraction
extended morphology
orthogonal subspace projection