DCENet-based low-light image enhancement improved by spiking encoding and convLSTM

DCENet-based low-light image enhancement improved by spiking encoding and convLSTM

The direct utilization of low-light images hinders downstream visual tasks. Traditional low-light image enhancement (LLIE) methods, such as Retinex-based networks, require image pairs. A spiking-coding methodology called intensity-to-latency has been used to gradually acquire the structural characte...

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Bibliographic Details
Main Authors: Xinghao Wang, Qiang Wang, Lei Zhang, Yi Qu, Fan Yi, Jiayang Yu, Qiuhan Liu, Ruicong Xia, Ziling Xu, Sirong Tong
Format: Article
Language:English
Published: Frontiers Media S.A. 2024-03-01
Series:Frontiers in Neuroscience
Subjects:
intensity-to-latency
spiking encoding
low-light enhancement
unpaired image
deep learning
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2024.1297671/full

Internet

https://www.frontiersin.org/articles/10.3389/fnins.2024.1297671/full

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