Learning a Simple Low-Light Image Enhancer from Paired Low-Light Instances-Reference-Cited by-同舟云学术

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Learning a Simple Low-Light Image Enhancer from Paired Low-Light Instances

Published:2023-06 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
language:
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Author:

Fu Zhenqi¹,Yang Yan²,Tu Xiaotong¹,Huang Yue¹,Ding Xinghao¹,Ma Kai-Kuang³

Affiliation:

1. School of Informatics, Xiamen University,Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China,China

2. School of Computer Science and Technology, Hangzhou Dianzi University,China

3. School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10203037/10203050/10203112.pdf?arnumber=10203112

Reference41 articles.

1. The Retinex Theory of Color Vision

2. SNR-Aware Low-light Image Enhancement

3. Enlightengan: Deep light enhancement without paired supervision;jiang;IEEE TIP,2021

4. STAR: A Structure and Texture Aware Retinex Model

5. Unsupervised Low-Light Image Enhancement Using Bright Channel Prior

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2. Enhancing low-light images via dehazing principles: Essence and method;Pattern Recognition Letters;2024-09

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4. A novel intuitionistic fuzzy generator for low-contrast color image enhancement technique;Information Fusion;2024-08

5. DANet: A Domain Alignment Network for Low-Light Image Enhancement;Electronics;2024-07-26

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