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A Survey of Deep Learning-Based Low-Light Image Enhancement [PDF]

open access: yesSensors, 2023
Images captured under poor lighting conditions often suffer from low brightness, low contrast, color distortion, and noise. The function of low-light image enhancement is to improve the visual effect of such images for subsequent processing.
Zhen Tian   +6 more
doaj   +4 more sources

Priori Knowledge Makes Low-Light Image Enhancement More Reasonable [PDF]

open access: yesSensors
This paper presents a priori knowledge-based low-light image enhancement framework, termed Priori DCE (Priori Deep Curve Estimation). The priori knowledge consists of two key aspects: (1) enhancing a low-light image is an ill-posed task, as the ...
Zefei Chen   +4 more
doaj   +2 more sources

Low‐light image enhancement for infrared and visible image fusion

open access: yesIET Image Processing, 2023
Infrared and visible image fusion (IVIF) is an essential branch of image fusion, and enhancing the visible image of IVIF can significantly improve the fusion performance. However, many existing low‐light enhancement methods are unsuitable for the visible
Yiqiao Zhou   +5 more
doaj   +2 more sources

Low-Light Image Enhancement Using Photometric Alignment with Hierarchy Pyramid Network [PDF]

open access: yesSensors, 2022
Low-light image enhancement can effectively assist high-level vision tasks that often fail in poor illumination conditions. Most previous data-driven methods, however, implemented enhancement directly from severely degraded low-light images that may ...
Jing Ye   +3 more
doaj   +2 more sources

Low-light image enhancement using generative adversarial networks [PDF]

open access: yesScientific Reports
In low-light environments, the amount of light captured by the camera sensor is reduced, resulting in lower image brightness. This makes it difficult to recognize or completely lose details in the image, which affects subsequent processing of low-light ...
Litian Wang   +3 more
doaj   +2 more sources

Decoupled Low-Light Image Enhancement [PDF]

open access: yesACM Transactions on Multimedia Computing, Communications, and Applications, 2022
The visual quality of photographs taken under imperfect lightness conditions can be degenerated by multiple factors, e.g., low lightness, imaging noise, color distortion, and so on. Current low-light image enhancement models focus on the improvement of low lightness only, or simply deal with all the degeneration factors as a whole, therefore leading to
Shijie Hao   +3 more
openaire   +2 more sources

Towards Low Light Enhancement With RAW Images [PDF]

open access: yesIEEE Transactions on Image Processing, 2022
In this paper, we make the first benchmark effort to elaborate on the superiority of using RAW images in the low light enhancement and develop a novel alternative route to utilize RAW images in a more flexible and practical way. Inspired by a full consideration on the typical image processing pipeline, we are inspired to develop a new evaluation ...
Haofeng Huang   +4 more
openaire   +3 more sources

Low-light Image Enhancement Model with Low Rank Approximation [PDF]

open access: yesJisuanji kexue, 2022
Due to the influence of low lightness,the images acquired at dim or backlight conditions tend to have poor visual quality.Retinex-based low-light enhancement models are effective in improving the scene lightness,but they are often limited in hand-ling ...
WANG Yi-han, HAO Shi-jie, HAN Xu, HONG Ri-chang
doaj   +1 more source

A survey on image enhancement for Low-light images

open access: yesHeliyon, 2023
In real scenes, due to the problems of low light and unsuitable views, the images often exhibit a variety of degradations, such as low contrast, color distortion, and noise. These degradations affect not only visual effects but also computer vision tasks. This paper focuses on the combination of traditional algorithms and machine learning algorithms in
Jiawei Guo   +4 more
openaire   +3 more sources

Multi-Feature Guided Low-Light Image Enhancement

open access: yesApplied Sciences, 2021
Due to the characteristics of low signal-to-noise ratio and low contrast, low-light images will have problems such as color distortion, low visibility, and accompanying noise, which will cause the accuracy of the target detection problem to drop or even ...
Hong Liang   +3 more
doaj   +1 more source

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