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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   +4 more sources

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   +2 more sources

Multi-Feature Guided Low-Light Image Enhancement [PDF]

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   +2 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

Pyramid Diffusion Models For Low-light Image Enhancement [PDF]

open access: yesProceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023
Recovering noise-covered details from low-light images is challenging, and the results given by previous methods leave room for improvement. Recent diffusion models show realistic and detailed image generation through a sequence of denoising refinements ...
Dewei Zhou, Zongxin Yang, Yi Yang
semanticscholar   +3 more sources

LIME: Low-Light Image Enhancement via Illumination Map Estimation

open access: yesIEEE Transactions on Image Processing, 2017
When one captures images in low-light conditions, the images often suffer from low visibility. Besides degrading the visual aesthetics of images, this poor quality may also significantly degenerate the performance of many computer vision and multimedia ...
Xiaojie Guo, Yu Li, Haibin Ling
semanticscholar   +4 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 Based on Generative Adversarial Network [PDF]

open access: yesFrontiers in Genetics, 2021
Image enhancement is considered to be one of the complex tasks in image processing. When the images are captured under dim light, the quality of the images degrades due to low visibility degenerating the vision-based algorithms’ performance that is built
Nandhini Abirami R.   +1 more
doaj   +2 more sources

Low-Light Image Enhancement Using Adaptive Digital Pixel Binning [PDF]

open access: yesSensors, 2015
This paper presents an image enhancement algorithm for low-light scenes in an environment with insufficient illumination. Simple amplification of intensity exhibits various undesired artifacts: noise amplification, intensity saturation, and loss of ...
Yoonjong Yoo, Jaehyun Im, Joonki Paik
doaj   +4 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
Hao, Shijie   +3 more
openaire   +2 more sources

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