国防科技大学学报2024，Vol.46Issue(2)：224-237,14.DOI:10.11887/j.cn.202402023
金字塔渐进融合低照度图像增强网络
Pyramid asymptotic fusion low-illumination image enhancement network
摘要
Abstract
Since existing low-illumination image enhancement networks have insufficient ability to perceive and express feature information of different scales,a low-illumination image enhancement network model based on pyramid asymptotic fusion was proposed.The network performed multiple down-sampling operations on the image to form a feature pyramid.It fused the feature maps at different scales by adding skip connections to three different branches of the feature pyramid.Fine recovery module further extracted the refined information,and restored the feature map to a normal light image.Results indicate that,the network model not only effectively enhances the brightness of the overall low-illumination image,but also maintains the detailed information and clear edge contours of the objects in the image.Moreover,it can effectively suppress the dark noise,and make the overall enhanced image realistic and natural.关键词
低照度图像增强/深度学习/特征金字塔/多尺度特征/跳跃连接Key words
low-illumination image enhancement/deep learning/feature pyramid/multi-scale features/skip connection分类
信息技术与安全科学引用本文复制引用
余映,徐超越,李淼,何鹏浩,杨昊..金字塔渐进融合低照度图像增强网络[J].国防科技大学学报,2024,46(2):224-237,14.基金项目
国家自然科学基金资助项目(62166048,61263048) （62166048,61263048）
云南省应用基础研究计划资助项目(2018FB102) （2018FB102）
云南大学"中青年骨干教师培养计划"资助项目(XT412003) （XT412003）
