Results 41 to 50 of about 157,053 (258)

Channel splitting attention network for low‐light image enhancement

open access: yesIET Image Processing, 2022
Low‐light enhancement is a crucial task in computer vision because of the limited dynamic range of digital imaging devices in poor lighting conditions. Images taken under low‐light conditions often suffer from insufficient brightness and severe noise. At
Bibo Lu   +3 more
doaj   +1 more source

Low-Illumination Image Enhancement Based on Deep Learning Techniques: A Brief Review

open access: yesPhotonics, 2023
As a critical preprocessing technique, low-illumination image enhancement has a wide range of practical applications. It aims to improve the visual perception of a given image captured without sufficient illumination.
Hao Tang   +5 more
doaj   +1 more source

Enhancing Low-Light Images Using Infrared Encoded Images

open access: yes2023 IEEE International Conference on Image Processing (ICIP), 2023
Low-light image enhancement task is essential yet challenging as it is ill-posed intrinsically. Previous arts mainly focus on the low-light images captured in the visible spectrum using pixel-wise loss, which limits the capacity of recovering the brightness, contrast, and texture details due to the small number of income photons.
Shulin Tian   +5 more
openaire   +2 more sources

Convolutional Neural Network-Based Low Light Image Enhancement Method

open access: yesКомпьютерная оптика
With advances in science and technology, remote sensing images are vital for vegetation monitoring. The use of remote sensing allows for the collection of widespread, multi-temporal data on vegetation, leading to a better comprehension and management of ...
M.X. Li, C.J. Xu
doaj   +3 more sources

Endoscopic image enhancement with noise suppression

open access: yesHealthcare Technology Letters, 2018
Stereoscopic endoscopes have been used increasingly in minimally invasive surgery to visualise the organ surface and manipulate various surgical tools. However, insufficient and irregular light sources become major challenges for endoscopic surgery.
Wenyao Xia   +2 more
doaj   +1 more source

MAGAN: Unsupervised Low-Light Image Enhancement Guided by Mixed-Attention

open access: yesBig Data Mining and Analytics, 2022
Most learning-based low-light image enhancement methods typically suffer from two problems. First, they require a large amount of paired data for training, which are difficult to acquire in most cases.
Renjun Wang   +4 more
doaj   +1 more source

Low Light Image Enhancement for Dark Images [PDF]

open access: yesInternational Journal of Data Science and Analysis, 2020
Image plays an important role in this present technological world and leads to progress in multimedia communication, various research fields related to image processing, etc. Low-light image enhancement specifically addresses images captured in low-light conditions such as nighttime, where the common goal is to brighten and improve the contrast of the ...
Akshay Patil   +4 more
openaire   +1 more source

LiCENt: Low-Light Image Enhancement Using the Light Channel of HSL

open access: yesIEEE Access, 2022
Images captured in low-brightness environments often lead to poor visibility and exhibit artifacts such as low brightness, low contrast, and color distortion.
Atik Garg, Xin-Wen Pan, Lan-Rong Dung
doaj   +1 more source

Semantically Contrastive Learning for Low-Light Image Enhancement

open access: yesProceedings of the AAAI Conference on Artificial Intelligence, 2022
Low-light image enhancement (LLE) remains challenging due to the unfavorable prevailing low-contrast and weak-visibility problems of single RGB images. In this paper, we respond to the intriguing learning-related question -- if leveraging both accessible unpaired over/underexposed images and high-level semantic guidance, can improve the performance of ...
Dong Liang 0008   +7 more
openaire   +2 more sources

Pyramid Diffusion Models for Low-light Image Enhancement

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 and motivate us to introduce them to low-light image enhancement for recovering realistic details ...
Dewei Zhou, Zongxin Yang, Yi Yang 0001
openaire   +2 more sources

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