Results 41 to 50 of about 23,223,534 (244)

DEANet: Decomposition Enhancement and Adjustment Network for Low-Light Image Enhancement

Tsinghua Science and Technology, 2023
Poor illumination greatly affects the quality of obtained images. In this paper, a novel convolutional neural network named DEANet is proposed on the basis of Retinex for low-light image enhancement.
Yonglong Jiang, Liangliang Li, Jiahe Zhu, Yuan Xue, Hongbing Ma   +4 more
doaj   +1 more source

Text in the dark: Extremely low-light text image enhancement [PDF]

Extremely low-light text images pose significant challenges for scene text detection. Existing methods enhance these images using low-light image enhancement techniques before text detection.
Lin, Che-Tsung,, Ng, Chun Chet,, Nah, Wan Jun,, Long Kew, Jie,, Hsu, Pohao,, Wang, Xinyu,, Tan, Zhi Qin,, Zach, Christopher,, Lai, Shang Hong,, Seng Chan, Chee,, Lin, Che-Tsung, Wang, Xinyu, Zach, Christopher, Lai, Shang Hong, Hsu, Pohao, Tan, Zhi Qin, Nah, Wan Jun, Chan, Chee Seng, Kew, Jie Long, Ng, Chun Chet   +19 more
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LiCENt: Low-Light Image Enhancement Using the Light Channel of HSL

IEEE 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

Enhancing Low-Light Images Using Infrared Encoded Images

2023 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, Yufei Wang 0006, Renjie Wan, Wenhan Yang, Alex C. Kot, Bihan Wen   +5 more
openaire   +3 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   +3 more sources

Low Light Image Enhancement for Dark Images [PDF]

International 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, Tejas Chaudhari, Ketan Deo, Kalpesh Sonawane, Rupali Bora   +4 more
openaire   +1 more source

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

Simplifying Low-Light Image Enhancement Networks with Relative Loss Functions [PDF]

, 2023
Image enhancement is a common technique used to mitigate issues such as severe noise, low brightness, low contrast, and color deviation in low-light images.
Wu, Junde, Wang, Yue, Xu, Yanwu, Di, Xiaoguang, Zhang, Yu, Li, Yong, Yang, Guohui, Wang, Chunhui, Fu, Rao   +8 more
core  

Delaunay triangulation based image enhancement for echocardiography images [PDF]

, 2009
A novel image enhancement approach for automatic echocardiography image processing is proposed. The main steps include undecimated wavelet based speckle noise reduction, edge detection, followed by a regional enhancement process that employs Delaunay ...
Ahanathapillai, V., Sonecki, P., Soraghan, J.J.   +2 more
core   +2 more sources

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