Weighted Sparse Representation and Gradient Domain Guided Filter Pyramid Image Fusion Based on Low-Light-Level Dual-Channel Camera

被引:15
|
作者
Chen, Guo [1 ]
Li, Li [1 ]
Jin, Weiqi [1 ,2 ]
Qiu, Su [1 ]
Guo, Hui [2 ]
机构
[1] Beijing Inst Technol, MOE Key Lab Optoelect Imaging Technol & Syst, Beijing 100081, Peoples R China
[2] Sci & Technol Low Light Level Night Vis Lab, Xian 710065, Shaanxi, Peoples R China
来源
IEEE PHOTONICS JOURNAL | 2019年 / 11卷 / 05期
关键词
Weighted sparse representation; gradient domain guided filter; image fusion; high dynamic range; PERFORMANCE;
D O I
10.1109/JPHOT.2019.2935134
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Generally, the dynamic range of night vision scenes is large. Owing to the limited dynamic range of traditional low light imaging technology, the captured images are always partially overexposed or underexposed. Multi-exposure fusion is the most effective method of overcoming the dynamic range limitation of sensor, and multi-frame low dynamic range (LDR) image fusion is a key consideration. However, existing fusion methods have problems such as image detail blurring and image aliasing. This paper proposes an image multi-scale decomposition method based on gradient domain guided filter (GDGF), which can better extract image details. The fusion algorithm adopts different fusion strategies for different scales. The low-frequency layer of the image uses a new weighted sparse representation (wSR) method, which can eliminate the image boundary problems and more adequately retain the image edges.
引用
收藏
页数:15
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