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基于优化N-FINDR算法的高光谱遥感影像矿物识别 被引量：3

Mineral Identification Based on the Optimized N-FINDR Algorithm of Hyperspectral Remote Sensing Images
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摘要 为了提高矿物识别的精度,利用高光谱遥感数据,运用线性光谱混合模型(LSMM)和优化的N-FINDR算法对Cuprite地区的AVIRIS和HYMAP数据进行端元提取,并进行矿物精细分类识别。实验表明:线性光谱混合模型易于操作,优化的端元提取算法优于传统交互式端元提取,可用于矿物成分的精细识别。 In order to improve the accuracy of mineral identification,use the Cuprite regional AVIRIS and HYMAP hyperspectral data to extract the mineral end members based on LSMM and a optimized N-FINDR algorithm,and accurately identify minerals.Experiments show that：Linear spectral mixture model is easy to operate,the optimized N-FINDR algorithm is superior to traditional interactive end member extraction method,recommend for fine identification of the mineral composition.
作者 钱进 邓喀中 刘冬
机构地区 江苏省资源环境信息工程重点实验室 国土环境与灾害监测国家测绘局重点实验室
出处 《金属矿山》 CAS 北大核心 2012年第8期84-87,91,共5页 Metal Mine
基金 国家自然科学基金项目(编号:41071273) 高等学校博士学科点专项科研基金项目(编号:20090095110002) 中央高校基本科研业务费专项资金项目(编号:2010QNA21) 国土环境与灾害监测国家测绘局重点实验室开放基金项目(编号:LEDM2011B07) 江苏省高校优势学科建设工程项目(编号:SA1102)
关键词 高光谱遥感 矿物识别 线性光谱混合模型 端元提取 Hyperspectral remote sensing Mineral identification Linear spectral mixture model End member extraction
分类号 TP391.9 [自动化与计算机技术—计算机应用技术]
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参考文献10

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二级参考文献35

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共引文献145

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金属矿山
2012年 第8期

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