Huihui Ju, Zhigang Liu, Yang Wang. Hyperspectral Anomaly Detection Algorithm Based on Combination of Spectral and Spatial Information[J]. Laser & Optoelectronics Progress, 2018, 55(12): 122801
- Laser & Optoelectronics Progress
- Vol. 55, Issue 12, 122801 (2018)
Fig. 1. Illustration of calculating pixel's spectral anomaly index and spatial structure anomaly index
Fig. 2. Flow chart of SSAD algorithm
Fig. 3. Experimental data 1. (a) Grey-scale map of the 130th band image; (b) spatial distribution map of targets
Fig. 4. Experimental data 2. (a) Grey-scale map of the 30th band image; (b) spatial distribution map of targets
Fig. 5. Experimental data 3. (a) Grey-scale map of the 100th band image; (b) spatial distribution map of targets
Fig. 6. Comparison of detection results on data 1 with different anomaly detection algorithms. (a) RX algorithm; (b) CRD algorithm; (c) LSMAD algorithm; (d) SSAD algorithm
Fig. 7. Comparison of detection results on data 2 with different anomaly detection algorithms. (a) RX algorithm; (b) CRD algorithm; (c) LSMAD algorithm; (d) SSAD algorithm
Fig. 8. Comparison of detection results on data 3 with different anomaly detection algorithms. (a) RX algorithm; (b) CRD algorithm; (c) LSMAD algorithm; (d) SSAD algorithm
Fig. 9. Comparison of ROC curves for different anomaly detection algorithms. (a) Data 1; (b) data 2; (c) data 3
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Table 1. Effect of inner window size on SSAD algorithm detection performance
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Table 2. AUC and execution time of different anomaly detection algorithms
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