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

测绘学报 ›› 2014, Vol. 43 ›› Issue (10): 1068-1074.doi: 10.13485/j.cnki.11-2089.2014.0171

压缩感知和万有引力模型相结合的高光谱混合像元分解

杨可明,王林伟,刘士文,刘飞,史钢强,赵思亮

中国矿业大学（北京）

收稿日期:2013-12-03 修回日期:2014-06-24 出版日期:2014-10-20 发布日期:2014-10-24
通讯作者: 杨可明 E-mail:ykm69@163.com
基金资助:
矿区环境重金属污染的高光谱遥感监测与分析方法研究

Hyperspectral Pixel Unmixing Combined with the Compressive Sensing and the Universal Gravitation Model

YANG Keming,WANG Linwei,LIU Shiwen,LIU Fei,SHI Gangqiang,ZHAO Siliang

College of Geosciences and Survey Engineering, China University of Mining & Technology (Beijing)

Received:2013-12-03 Revised:2014-06-24 Online:2014-10-20 Published:2014-10-24
Contact: YANG Keming E-mail:ykm69@163.com

摘要/Abstract

摘要：

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（Compressive Sensing，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（Universal Gravitation Model，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。

关键词: 压缩感知, 万有引力模型, 混合像元分解, 端元提取, 丰度反演

Abstract:

Hyperspectral imagery has the characteristic of high spectral resolution, but the low spatial resolution makes the mixed pixels exist ubiquitously in them. Pixel unmixing is the

?important content in the field of hyperspectral remote sensing application, including abundance extracting and abundance inversing. Based on the compressive sensing (CS)

theory, combined with neural network technology, a novel hyperspectral endmember extracting model based on the compressive sensing theory is proposed. After that,

applied the classic Universal Gravitation Model (UGM) into abundance inversing, an abundance inversing algorithm based on the universal gravitation model is put forward.

Finally, the model and the algorithm are realized in MATLAB with the Hyperion hyperspectral image and the accuracy of the endmember is assessed and analyzed

according to the results. Experimental results show that the proposed extracting model and inversing algorithm have a certain degree of feasibility in both theory and practice,

at the same time the computational accuracy meets the requirements.

Key words: compressive sensing, universal gravitation model, pixel unmixing, endmember extracting, abundance inversing

中图分类号:

TP 7

杨可明王林伟刘士文刘飞史钢强赵思亮. 压缩感知和万有引力模型相结合的高光谱混合像元分解[J]. 测绘学报, 2014, 43(10): 1068-1074.

YANG Keming WANG Linwei LIU Shiwen LIU Fei SHI Gangqiang ZHAO Siliang. Hyperspectral Pixel Unmixing Combined with the Compressive Sensing and the Universal Gravitation Model[J]. Acta Geodaetica et Cartographica Sinica, 2014, 43(10): 1068-1074.

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压缩感知和万有引力模型相结合的高光谱混合像元分解

Hyperspectral Pixel Unmixing Combined with the Compressive Sensing and the Universal Gravitation Model

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