Cross-level feature adaptive fusion network for low-light image enhancement
Image Processing|更新时间:2024-06-27
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Cross-level feature adaptive fusion network for low-light image enhancement
“In the field of image processing, experts have proposed a low light image enhancement algorithm that effectively improves image brightness and contrast through cross level feature adaptive fusion, providing a new solution for improving image quality in low light environments.”
Chinese Journal of Liquid Crystals and DisplaysVol. 39, Issue 6, Pages: 856-866(2024)
作者机构:
江西理工大学 电气工程与自动化学院, 江西 赣州 341000
作者简介:
基金信息:
National Natural Science Foundation of China(51365017;61463018);General Project of Natural Science Foundation of Jiangxi Province(20192BAB205084);Jiangxi Provincial Department of Education Science and Technology Research Key Project(GJJ170491)
LIANG Liming, ZHU Chenkun, YANG Yuan, et al. Cross-level feature adaptive fusion network for low-light image enhancement[J]. Chinese journal of liquid crystals and displays, 2024, 39(6): 856-866.
DOI:
LIANG Liming, ZHU Chenkun, YANG Yuan, et al. Cross-level feature adaptive fusion network for low-light image enhancement[J]. Chinese journal of liquid crystals and displays, 2024, 39(6): 856-866. DOI: 10.37188/CJLCD.2023-0210.
Cross-level feature adaptive fusion network for low-light image enhancement