• Electronics Optics & Control
  • Vol. 24, Issue 6, 53 (2017)
CHANG Hong-wei, WANG Tao, FANG Hao, and WU Zhi-lin
Author Affiliations
  • [in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2017.06.011 Cite this Article
    CHANG Hong-wei, WANG Tao, FANG Hao, WU Zhi-lin. A Hyperspectral Anomaly Detection Algorithm Based on Edge Expansion and Local Summation[J]. Electronics Optics & Control, 2017, 24(6): 53 Copy Citation Text show less
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    [4] KWON H, NASRABADI N M. Kernel RX algorithm: a nonlinear anomaly detector for hyperspectral imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2005, 43(2): 388-397.

    [6] BANERJEE A, BURLINA P. A support vector method for anomaly detection in hyperspectral imagery[J]. IEEE Transactions on Geoscience Remote sensing, 2006, 44(8): 2282-2285.

    [7] ZARE-BAGHBIDI M, HOMAYOUNI S, JAMSHIDI K. Improving the RX anomaly detection algorithm for hyperspectral images using FFT[J]. Journal of Modeling & Simulation in Electrical & Electronics Engineering, 2015, 1(2): 33-38.

    [9] JABLONSKI J A, BIHL T J, BAUER K W. Principal component reconstruction error for hyperspectral anomaly detection[J]. IEEE Geoscience and Remote Sensing Letters, 2015, 12(8): 1725-1728.

    CHANG Hong-wei, WANG Tao, FANG Hao, WU Zhi-lin. A Hyperspectral Anomaly Detection Algorithm Based on Edge Expansion and Local Summation[J]. Electronics Optics & Control, 2017, 24(6): 53
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