Divide and conquer: Ill-light image enhancement via hybrid deep network
作者：
Highlights：
• Low and ill-light image enhancement.
• Lowlight mage enhancement without paired training data supervision.
• Image enhancement with a few-shots of training data.
• Deep hybrid learning, independent of the type of training and test data.
• First Large scale dataset for ill-lighting conditions.
摘要
•Low and ill-light image enhancement.•Lowlight mage enhancement without paired training data supervision.•Image enhancement with a few-shots of training data.•Deep hybrid learning, independent of the type of training and test data.•First Large scale dataset for ill-lighting conditions.
论文关键词：Low light imaging,Intelligent systems,Adaptive enhancement,Few-shot learning
论文评审过程：Received 18 December 2020, Revised 11 February 2021, Accepted 9 April 2021, Available online 6 May 2021, Version of Record 21 May 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.115034
