Results 41 to 50 of about 166,446 (292)

Channel splitting attention network for low‐light image enhancement

IET 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, Zebang Pang, Yanan Gu, Yanmei Zheng   +3 more
doaj   +1 more source

Semantically Contrastive Learning for Low-Light Image Enhancement

Proceedings 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, Ling Li 0010, Mingqiang Wei, Shuo Yang, Liyan Zhang, Wenhan Yang, Yun Du, Huiyu Zhou 0001   +7 more
openaire   +2 more sources

Pyramid Diffusion Models for Low-light Image Enhancement

Proceedings 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

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

Photonics, 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, Hongyu Zhu, Linfeng Fei, Tingwei Wang, Yichao Cao, Chao Xie   +5 more
doaj   +1 more source

Gradient-Based Low-Light Image Enhancement [PDF]

2019 IEEE International Conference on Consumer Electronics (ICCE), 2019
A low-light image enhancement is a highly demanded image processing technique, especially for consumer digital cameras and cameras on mobile phones. In this paper, a gradient-based low-light image enhancement algorithm is proposed. The key is to enhance the gradients of dark region, because the gradients are more sensitive for human visual system than ...
Masayuki Tanaka 0001, Takashi Shibata 0001, Masatoshi Okutomi   +2 more
openaire   +2 more sources

Invertible network for unpaired low-light image enhancement

The Visual Computer, 2023
Existing unpaired low-light image enhancement approaches prefer to employ the two-way GAN framework, in which two CNN generators are deployed for enhancement and degradation separately. However, such data-driven models ignore the inherent characteristics of transformation between the low and normal light images, leading to unstable training and ...
Jize Zhang, Haolin Wang 0004, Xiaohe Wu, Wangmeng Zuo   +3 more
openaire   +2 more sources

PESiT: Progressive Joint Enhancement and Blind Super-Resolution for Low-Light and Low-Resolution Images Under Total Variation Constraints

IEEE Access
Traditional enhancement techniques can improve the contrast of low-light and low-resolution images, but they fail to recover their resolution. Conversely, traditional super-resolution (SR) algorithms can enhance resolution but not restore contrast.
He Deng, Kai Cheng, Yuqing Li
doaj   +1 more source

DEEP LEARNING-BASED LOW LIGHT IMAGE ENHANCEMENT FOR IMPROVED VISIBILITY

, 2023
Low light conditions pose significant challenges for image capture and processing, leading to degraded image quality with reduced visibility and increased noise.
N.Baby rani, A. Joshna, B. Neelima, Ch. Varsha, G. Nikitha
core   +1 more source

DeepSelfie: Single-Shot Low-Light Enhancement for Selfies

IEEE Access, 2020
Taking a high-quality selfie photo in a low-light environment is challenging. Because the foreground and background often have different illumination conditions, they suffer heavily from over/under-exposure issues and cannot be treated in the same manner
Yucheng Lu, Dong-Wook Kim, Seung-Won Jung   +2 more
doaj   +1 more source

Content-illumination coupling guided low-light image enhancement network. [PDF]

Sci Rep
Current low-light enhancement algorithms fail to suppress noise when enhancing brightness, and may introduces structural distortion and color distortion caused by halos or artifacts.
Zhao R, Xie M, Feng X, Su X, Zhang H, Yang W.   +5 more
europepmc   +2 more sources