| 基于独立成分分析的高光谱变化检测 |
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| 引用本文： | 武辰,杜博,张良培.基于独立成分分析的高光谱变化检测[J].遥感学报,2012,16(3):545-561. |
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| 作者姓名： | 武辰 杜博 张良培 |
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| 作者单位： | 武汉大学 测绘遥感信息工程国家重点实验室, 湖北 武汉 430079;武汉大学 计算机学院, 湖北 武汉 430072;武汉大学 测绘遥感信息工程国家重点实验室, 湖北 武汉 430079 |
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| 基金项目： | 国家重点基础研究发展计划(973计划)(编号:2011CB707105);国家自然科学基金(编号:40930532,61102128,41061130553);中国科学院数字地球重点实验室开放基金(编号:2010LDE006);中国博士后科学基金(编号:211-180788);湖北省自然科学基金(编号:2011CDB455);中央高校基本科研业务费专项资金(编号:211274633) |
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| 摘 要： | 现有的变化检测方法并未充分研究变化前后高光谱遥感影像端元的联系,不能准确地分析地物变化信息。本文提出了一种基于独立成分分析的高光谱遥感影像变化检测方法,对差值影像进行基于偏斜度的独立成分分析,在不同组分图中分别显示单一地物的变化情况,进而提取变化信息。实验表明,该方法能够在获得较高检测率的同时维持较低的误检率,检测效果优于传统方法。
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| 关 键 词： | 高光谱遥感影像 变化检测 独立成分分析 偏斜度 差值影像 |
| 收稿时间： | 2011/4/21 0:00:00 |
| 修稿时间： | 2011/7/29 0:00:00 |
Hyperspectral change detection based on independent component analysis |
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| WU Chen,DU Bo and ZHANG Liangpei.Hyperspectral change detection based on independent component analysis[J].Journal of Remote Sensing,2012,16(3):545-561. |
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| Authors: | WU Chen DU Bo and ZHANG Liangpei |
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| Institution: | State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;School of Computer, Wuhan University, Wuhan 430072, China;State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China |
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| Abstract: | Change detection is the process of analyzing changes of surface features with multi-temporal remote sensing imagery of the same area. Hyperspectral remote sensing images contain abundant spectral information for accurate change detection, which, regrettably, is not fully taken into account by existing approaches. In this paper, a hyperspectral change detection method based on Independent Component Analysis (ICA) is investigated. The difference image is analyzed by skew-based ICA. The change of a single feature can be obtained and then the change is extracted from each abundance image. Experiment results demonstrate that the ICA-based hyperspectral change detection performs better than other traditional methods with a high detection rate and a low false detection rate. |
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| Keywords: | hyperspectral remote sensing image change detection ICA skew difference image |
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