Wei Li, Zhongmin Li. NSST-Based Perception Fusion Method for Infrared and Visible Images[J]. Laser & Optoelectronics Progress, 2021, 58(20): 2010014
- Laser & Optoelectronics Progress
- Vol. 58, Issue 20, 2010014 (2021)
Fig. 1. Dcomposition process of NSST multi-scale and multi-directional
Fig. 2. Structure of simple PA-PCNN model
Fig. 3. Pixel logarithmic sub-image obtained by two-layer decomposition of low-frequency image. (a) D(1,0); (b) D(1,1); (c) D(2,0); (d) D(2,1)
Fig. 4. Basic framework of fusion method
Fig. 5. Fusion results under different μ values. (a) μ→0; (b) μ=10; (c) μ=30; (d) μ=50; (e) μ=100; (f) μ=300; (g) μ=500; (h) μ→+¥
Fig. 6. Fusion results of different methods under “Kayak” image. (a) IR image; (b) VIS image; (c) PCA method; (d) LatLRR method; (e) MSD method; (f) PCNN method; (g) PA-PCNN method; (h) proposed method
Fig. 7. Fusion results of different methods under “Road” image. (a) IR image; (b) VIS image; (c) PCA method; (d) LatLRR method; (e) MSD method; (f) PCNN method; (g) PA-PCNN method; (h) proposed method
Fig. 8. Fusion results of different methods under “Steamboard” image. (a) IR image; (b) VIS image; (c) PCA method; (d) LatLRR method; (e) MSD method; (f) PCNN method; (g) PA-PCNN method; (h) proposed method
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Table 1. Mean values of objective evaluation index by different methods
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