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Finding Hyperspectral Anomalies Using Multivariate Outlier Detection

机译：使用多变量异常检测找到高光谱异常

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This research demonstrates the adverse implications of using non-robust statistical methods for detecting anomalies in hyperspectral image data, and proposes the use of multivariate outlier detection methods as an alternative detection strategy. Existing outlier detection methods are adapted for use in a hyperspectral image context, and their performance is compared to the benchmark RX detector and a cluster-based anomaly detector. Tests conducted using both simulated data and actual hyperspectral imagery indicate that multivariate outlier detection methods can achieve superior detection performance relative to current non-robust detection methods.

机译：该研究展示了使用非鲁棒统计方法来检测高光谱图像数据中的异常的不稳健统计方法的不利影响，并提出使用多变量异常检测方法作为替代检测策略。现有的异常检测方法适用于高光谱图像上下文，并将其性能与基于基于基于基于基于群集的异常检测器进行比较。使用模拟数据和实际高光谱图像进行的测试表明多变量异常值检测方法可以相对于电流非鲁棒检测方法实现卓越的检测性能。

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《IEEE Aerospace Conference》|2007年||共24页
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Timothy E. Smetek; Kenneth W. Bauer; The Institute of Electrical and Electronics EngineersInc.;
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中图分类 V1-53;
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1. Outlier detection in hyperspectral imagery using closest distance to center with ellipsoidal multivariate trimming [J] . Ryan F Caulk, Kevin B Reyes, Kenneth W Bauer Journal of defense modeling and simulatio . 2012,第2期

机译：使用椭圆形多元修剪法使用离中心最近的距离在高光谱图像中进行异常检测
2. Hyperspectral Anomaly Detection Using Collaborative Representation With Outlier Removal [J] . Su Hongjun, Wu Zhaoyue, Du Qian, Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of . 2018,第12期

机译：使用协同表示和异常值消除的高光谱异常检测
3. Comparing compositional multivariate outliers with autoencoder networks in anomaly detection at Hamich exploration area, east of Iran [J] . Moeini Hamid, Torab Farhad Mohammad Journal of Geochemical Exploration: Journal of the Association of Exploration Geochemists . 2017,第期

机译：在伊朗东部的Hamich探索区对Automaly探测中的AutoEncoder网络进行组成多元异常因素
4. Finding Hyperspectral Anomalies Using Multivariate Outlier Detection [C] . Timothy E. Smetek, Kenneth W. Bauer, The Institute of Electrical and Electronics EngineersInc. IEEE Aerospace Conference . 2007

机译：使用多变量异常检测找到高光谱异常
5. Hyperspectral imagery target detection using improved anomaly detection and signature matching methods. [D] . Smetek, Timothy E. 2007

机译：使用改进的异常检测和签名匹配方法进行高光谱图像目标检测。
6. Early Detection of Tomato Spotted Wilt Virus by Hyperspectral Imaging and Outlier Removal Auxiliary Classifier Generative Adversarial Nets (OR-AC-GAN) [O] . Dongyi Wang, Robert Vinson, Maxwell Holmes, -1

机译：通过高光谱成像和异常去除辅助分类器生成对抗网络（OR-AC-GAN）早期发现番茄斑萎病毒
7. Finding Hyperspectral Anomalies Using Multivariate Outlier Detection [O] . Timothy E. Smetek, Kenneth W. Bauer 2009

机译：利用多元离群点检测发现高光谱异常
8. Outlier Detection in Hyperspectral Imagery Using Closest Distance to Center with Ellipsoidal Multivariate Trimming [R] . Caulk, R. F., Reyes, K. B., Bauer, J. K. 2011

机译：利用椭球多变量修剪最近距离中心的高光谱图像离群检测

Finding Hyperspectral Anomalies Using Multivariate Outlier Detection

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