Name
Abstract | ||
|---|---|---|
Low-light images often suffer from poor quality and low visibility. Improving the quality of low-light image is becoming a highly desired subject in both computational photography and computer vision applications. This paper proposes an effective method to constrain the illumination map t by estimating the norm and constructing the constraint coefficients, which called LieCNE. More specifically, we estimate the initial illumination map by finding the maximum value of R, G and B channels and optimize it by norm estimation. We propose a function t. to contain the exponential power. in order to optimize the enhancement effect under different illumination conditions. Finally, a new evaluation criterion is also proposed. We use the similarity with the true value to determine the enhanced effect. Experimental results show that LieCNE exhibits better performance under a variety of lighting conditions in enhancement results and image spillover prevention. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-981-10-7299-4_30 | Communications in Computer and Information Science |
Keywords | DocType | Volume |
Low-light image enhancement,Illumination optimization,Norm estimate,Quadtree algorithm | Conference | 771 |
ISSN | Citations | PageRank |
1865-0929 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tan Zhao | 1 | 0 | 0.34 |
| Hui Ding | 2 | 88 | 8.86 |
| Yuanyuan Shang | 3 | 210 | 16.83 |
| Xiuzhuang Zhou | 4 | 380 | 20.26 |