| 基于局域自适应信息理论测度学习的高光谱目标探测方法 |
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| 引用本文： | 董燕妮,杜博,张乐飞,张良培.基于局域自适应信息理论测度学习的高光谱目标探测方法[J].武汉大学学报(信息科学版),2018,43(8):1271-1277. |
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| 作者姓名： | 董燕妮 杜博 张乐飞 张良培 |
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| 作者单位： | 1.中国地质大学(武汉)地球物理与空间信息学院, 湖北 武汉, 430074 |
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| 基金项目： | 国家重点基础研究发展规划项目2012CB719905国家自然科学基金61471274国家自然科学基金41431175湖北省自然科学基金2014CFB193中央高校基本科研业务费专项资金CUG 170687 |
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| 摘 要： | 传统基于信号检测的目标探测方法需要依赖特定的统计假设，只有在符合条件的情况下才能取得较好的目标探测结果。为了克服这一缺陷，提出了一种基于局域自适应的信息理论测度学习方法。首先将信息理论测度学习方法作为目标主函数，然后加以局域自适应决策法则进行约束，自适应地减小相似样本对距离，增大不相似样本对距离，使得在考虑阈值的同时兼顾测度学习前后距离的改变情况来进行目标探测决策，从而更好地实现目标探测。实验证明，该方法与其他经典目标探测方法或测度学习方法相比，可以更好地实现目标与背景分离，能够更有效地对高光谱影像数据进行目标探测。
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| 关 键 词： | 目标探测 测度学习 决策法则 局域自适应 高光谱影像 |
| 收稿时间： | 2016-09-19 |
Hyperspectral Target Detection Based on Locally Adaptive Information-Theoretic Metric Learning Method |
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| Institution: | 1.Institute of Geophysics & Geomatics, China University of Geosciences, Wuhan 430074, China2.School of Computer Science, Wuhan University, Wuhan 430072, China3.State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China |
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| Abstract: | The classical target detection methods may only perform well with certain assumptions. To overcome the shortcomings, this paper proposes a novel local decision adaptive information-theoretic metric learning (LA-ITML) target detector. Firstly, the proposed method uses the ITML method as the objective function for learning a Mahalanobis distance to separate similar and dissimilar point-pairs. Then, a locally decision adaptive constraint is applied to shrink the distances between samples of similar pairs and expand the distances between samples of dissimilar pairs. Finally, we can make the detection decision by considering both the threshold and the changes between the distances before and after metric learning. The experimental results demonstrate that the proposed method can obviously separate target samples from background ones and out performs both the state-of-the-art target detection algorithms and the other classical metric learning methods. |
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