计算机工程与应用2024，Vol.60Issue(4)：200-210,11.DOI:10.3778/j.issn.1002-8331.2209-0470
结合稠密小波变换的双分支低照度图像增强
Dual-Branch Low-Light Image Enhancement Combined with Dense Wavelet Transform
摘要
Abstract
A dual-branch image enhancement method combining dense wavelet transform is proposed to solve the prob-lems of low brightness,high noise,and color distortion in low-light images.Firstly,dense wavelet networks are used for multi-scale feature information fusion to reduce information loss and provide denoising capability.Then,the global atten-tion module and feature extraction module are embedded in the multi-scale feature fusion to fully extract global and local features.Finally,the effect of low-light images is enhanced by color enhancement and detail reconstruction with a dual-branch structure.In addition,a new joint loss function is introduced to guide the network training from multiple aspects to enhance its performance.The experimental results show that the proposed method effectively improves the brightness of low-light images,suppresses image noise,and obtains richer details and color information.The enhanced images are clearer and more natural,and the peak signal-to-noise ratio and structural similarity have significant advantages over the main-stream methods.关键词
稠密小波变换/低照度/图像增强/双分支/联合损失函数Key words
dense wavelet/low-light/image enhancement/dual-branch/joint loss function分类
信息技术与安全科学引用本文复制引用
陈俊杰,周永霞,祖佳贞,盛威,赵平..结合稠密小波变换的双分支低照度图像增强[J].计算机工程与应用,2024,60(4):200-210,11.基金项目
浙江省自然科学基金(LY19F030013). （LY19F030013）
