期刊文献+

DEANet: Decomposition Enhancement and Adjustment Network for Low-Light Image Enhancement 被引量:1

原文传递
导出
摘要 Poor illumination greatly affects the quality of obtained images.In this paper,a novel convolutional neural network named DEANet is proposed on the basis of Retinex for low-light image enhancement.DEANet combines the frequency and content information of images and is divided into three subnetworks:decomposition,enhancement,and adjustment networks,which perform image decomposition;denoising,contrast enhancement,and detail preservation;and image adjustment and generation,respectively.The model is trained on the public LOL dataset,and the experimental results show that it outperforms the existing state-of-the-art methods regarding visual effects and image quality.
出处 《Tsinghua Science and Technology》 SCIE EI CAS CSCD 2023年第4期743-753,共11页 清华大学学报(自然科学版(英文版)
基金 This work was supported by the Shanghai Aerospace Science and Technology Innovation Fund(No.SAST2019-048) the Cross-Media Intelligent Technology Project of Beijing National Research Center for Information Science and Technology(BNRist)(No.BNR2019TD01022).
  • 相关文献

同被引文献1

引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部