Volume 42 Issue 11
Feb.  2014
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Liu Zhigang, Lu Yunlong, Wei Yiwei. Supervised method for hyperspectral image camouflage target detection[J]. Infrared and Laser Engineering, 2013, 42(11): 3076-3081.
Citation: Liu Zhigang, Lu Yunlong, Wei Yiwei. Supervised method for hyperspectral image camouflage target detection[J]. Infrared and Laser Engineering, 2013, 42(11): 3076-3081.

Supervised method for hyperspectral image camouflage target detection

  • Received Date: 2013-03-14
  • Rev Recd Date: 2013-04-15
  • Publish Date: 2013-11-25
  • Aiming at camouflage target detection problem, a supervised method for hyperspectral image camouflage target detection was proposed. The plant camouflage targets were taken as study objects, and then based on the spectral characteristics analysis of camouflage materials and plants, camouflage materials and plant's spectral differences were magnified through spectrum rearrangement, spectral derivative and spectrum difference enhancement. Then, principal components analysis(PCA) was used for dimensionality reduction, thus a detection method for big camouflage target in hyperspectral image was realized. The experimental result shows that the method outperforms weighted correlation matric-constrained energy minimization(WCM-CEM) and unsupervised target generation process-orthogonal subspace projection(UTGP-OSP) both in the detection time and detection result.
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Supervised method for hyperspectral image camouflage target detection

  • 1. The Second Artillery Engineering University,Xi'an 710025,China

Abstract: Aiming at camouflage target detection problem, a supervised method for hyperspectral image camouflage target detection was proposed. The plant camouflage targets were taken as study objects, and then based on the spectral characteristics analysis of camouflage materials and plants, camouflage materials and plant's spectral differences were magnified through spectrum rearrangement, spectral derivative and spectrum difference enhancement. Then, principal components analysis(PCA) was used for dimensionality reduction, thus a detection method for big camouflage target in hyperspectral image was realized. The experimental result shows that the method outperforms weighted correlation matric-constrained energy minimization(WCM-CEM) and unsupervised target generation process-orthogonal subspace projection(UTGP-OSP) both in the detection time and detection result.

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