Acta Optica Sinica, Volume. 38, Issue 12, 1228004(2018)
Hyperspectral Target Detection Based on Sparse Representation and Adaptive Model
Fig. 1. (a) Sparse representation without error vector; (b) sparse representation with error vector
Fig. 4. Synthetic data set. (a) Original target for synthesis; (b) synthetic image; (c) target truth map
Fig. 5. (a) AUC value at different sparsity levels; (b) ROC curves at different λ
Fig. 6. Detection results using different methods. (a) SRTD; (b) SRBBH; (c) SCBD-AWLM; (d) proposed method
Fig. 9. (a) AUC value at different sparsity levels; (b) ROC curves at different λ
Fig. 10. Detection results for AVIRIS dataset. (a) SRTD; (b) SRBBH; (c) SCBD-AWLM;(d) proposed method
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Feiyan Li, Hongtao Huo, Jie Bai, Wei Wang. Hyperspectral Target Detection Based on Sparse Representation and Adaptive Model[J]. Acta Optica Sinica, 2018, 38(12): 1228004
Category: Remote Sensing and Sensors
Received: Apr. 23, 2018
Accepted: Jul. 20, 2018
Published Online: May. 10, 2019
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