2021 IEEE International Conference on Image Processing
19-22 September 2021 • Anchorage, Alaska, USA
Imaging Without Borders
| Paper ID | TEC-1.9 | ||
| Paper Title | COLOR CHANNEL FUSION NETWORK FOR LOW-LIGHT IMAGE ENHANCEMENT | ||
| Authors | Lingchao Zhao, Xiaolin Gong, Kaihua Liu, Jian Wang, Bai Zhao, Yu Liu, Tianjin University, China | ||
| Session | TEC-1: Restoration and Enhancement 1 | ||
| Location | Area G | ||
| Session Time: | Tuesday, 21 September, 13:30 - 15:00 | ||
| Presentation Time: | Tuesday, 21 September, 13:30 - 15:00 | ||
| Presentation | Poster | ||
| Topic | Image and Video Processing: Restoration and enhancement | ||
| IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
| Abstract | When capturing images in low light condition, due to insufficient lighting, the true color information and texture details of objects are difficult to obtain. Considering that, we propose an end-to-end color channel fusion network (CCFN). Specifically, our proposed method uses partial channel combination inputs to obtain multiple enhancement results. The relevance among RGB channels is maintained by modeling channel interdependencies. Subsequently, a multi-scale feature channel shuffle module (MFCS) is designed to combine image features at different scales, which makes the fusion images hold more rich information. Finally, the output images are generated after detail enhancement. Extensive experiments demonstrate the superiority of our method over several state-of-the-arts in terms of enhancement quality. | ||