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测绘学报  2014 

压缩感知和万有引力模型相结合的高光谱混合像元分解

DOI: 10.13485/j.cnki.11-2089.2014.0171, PP. 1068-1074

Keywords: 压缩感知,万有引力模型,混合像元分解,端元提取,丰度反演

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Abstract:

高光谱影像虽然具有较高的光谱分辨率,但因其空间分辨率低而普遍存在混合像元。混合像元分解是高光谱遥感应用的重要研究内容,包括端元提取和端元丰度反演两部分。本文以压缩感知(CompressiveSensing,CS)理论为基础,结合神经网络技术提出了一种新的端元提取模型——基于CS的高光谱影像端元提取模型。同时,将经典的万有引力模型(UniversalGravitationModel,UGM)引入到端元丰度反演中,提出基于UGM的端元丰度反演算法。最后,以Hyperion高光谱影像为实验数据在MATLAB中对模型和算法进行编程实现,并对其结果进行精度评定。实验结果表明,本文提出的提取模型与反演算法无论在理论上还是在实际操作中,都具有一定的可行性,同时精度也满足要求。

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