Anomaly detection from hyperspectral imagery

被引:549
|
作者
Stein, DWJ [1 ]
Beaven, SG
Hoff, LE
Winter, EM
Schaum, AP
Stocker, AD
机构
[1] SPAWAR Syst Ctr, San Diego, CA USA
[2] Naval Res Lab, Washington, DC USA
[3] Space Comp Corp, Los Angeles, CA USA
关键词
D O I
10.1109/79.974730
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Anomaly detectors for hyperspectral data were developed based on fundamental detection theoretic principles, including the generalized likelihood ratio test (GLRT) and approximations thereof. As such, the underlying theory for the application of anomaly detection to systems with inherently high dimensionality was outlined. It was shown that the performance improves with SNR depends on the characteristics of the targets, clutter, environment, and sensor.
引用
收藏
页码:58 / 69
页数:12
相关论文
共 50 条
  • [21] Multipixel Anomaly Detection With Unknown Patterns for Hyperspectral Imagery
    Liu, Jun
    Hou, Zengfu
    Li, Wei
    Tao, Ran
    Orlando, Danilo
    Li, Hongbin
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2022, 33 (10) : 5557 - 5567
  • [22] Compression technique for hyperspectral imagery oriented anomaly detection
    Nian, Yong-Jian
    Wang, Zhan
    Wan, Jian-Wei
    Xin, Qin
    Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology, 2009, 31 (03): : 48 - 52
  • [23] Multiple Band Selection for Anomaly Detection in Hyperspectral Imagery
    Wang, Lin
    Chang, Chein-I
    2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, : 7022 - 7025
  • [24] Kernel-based anomaly detection in hyperspectral imagery
    Kwon, Heesung
    Nasrabadi, Nasser M.
    TRANSFORMATIONAL SCIENCE AND TECHNOLOGY FOR THE CURRENT AND FUTURE FORCE, 2006, 42 : 3 - +
  • [25] Study and Analysis on Anomaly Detection Methods for Hyperspectral Imagery
    Chen, Yuheng
    Zhou, Jiankang
    Chen, Xinhua
    Ji, Yiqun
    Shen, Weimin
    SIXTH INTERNATIONAL CONFERENCE ON OPTICAL AND PHOTONIC ENGINEERING (ICOPEN 2018), 2018, 10827
  • [26] Locality-Constrained Anomaly Detection for Hyperspectral Imagery
    Liu, Jiabin
    Li, Wei
    Du, Qian
    Liu, Kui
    INTERNATIONAL CONFERENCE ON INTELLIGENT EARTH OBSERVING AND APPLICATIONS 2015, 2015, 9808
  • [27] Saliency weighted RX hyperspectral imagery anomaly detection
    Liu J.
    Wang S.
    Liu W.
    Hu B.
    Yaogan Xuebao/Journal of Remote Sensing, 2019, 23 (03): : 418 - 430
  • [28] Multiple-Window Anomaly Detection for Hyperspectral Imagery
    Liu, Wei-Min
    Chang, Chein-I
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2013, 6 (02) : 644 - 658
  • [29] Unmixing component analysis for anomaly detection in hyperspectral imagery
    Gu, Yanfeng
    Ye, Zhang
    Ying, Liu
    2006 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP 2006, PROCEEDINGS, 2006, : 965 - +
  • [30] Progressive Band Processing of Anomaly Detection in Hyperspectral Imagery
    Chang, Chein-I
    Li, Yao
    Hobbs, Marissa C.
    Schultz, Robert C.
    Liu, Wei-Min
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2015, 8 (07) : 3558 - 3571