Fusion of the low-light-level visible and infrared images for night-vision context enhancement Download: 1060次
School of Optoelectronics, Beijing Institute of Technology, Beijing 100081, China
Figures & Tables
Fig. 1. The proposed infrared and visible image FNCE.
下载图片 查看原文
Fig. 2. Test pairs of visible and infrared images captured under low-light-level conditions. (a) “Queen’s Road,” (b) “Buildings.”
下载图片 查看原文
Fig. 3. Adaptive brightness stretching method.
下载图片 查看原文
Fig. 4. Initial enhancement results for the “Queen’s Road” visible image. (a) The original, (b) result with Zhou’s method[7], and (c) result with the proposed method.
下载图片 查看原文
Fig. 5. Structure of the hybrid MSD with the GF and the GDGF.
下载图片 查看原文
Fig. 6. Fusion results of different methods for the test images.
下载图片 查看原文
Table1. Quantitative Assessments of Different Methods
Method | IE | AG | | PS | VIFF |
---|
GFF | 6.6093 | 0.0100 | 0.6132 | 16.4800 | 0.4278 | GTF | 6.3275 | 0.0061 | 0.2847 | 13.7586 | 0.2205 | GFCE | 6.8106 | 0.0152 | 0.3612 | 19.5798 | 0.5648 | FNCE | 6.9786 | 0.0187 | 0.6029 | 20.6976 | 0.6580 |
|
查看原文
Table2. Average Running Time on 640 × 480 Images
Method | GFF | GTF | GFCE | FNCE |
---|
Time (s) | 0.526 | 6.833 | 1.605 | 2.069 |
|
查看原文
Jin Zhu, Weiqi Jin, Li Li, Zhenghao Han, Xia Wang. Fusion of the low-light-level visible and infrared images for night-vision context enhancement[J]. Chinese Optics Letters, 2018, 16(1): 013501.