Results 31 to 40 of about 942 (213)
Endoscopic image enhancement with noise suppression
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
Semantically Contrastive Learning for Low-Light Image Enhancement
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
Low-Illumination Image Enhancement Based on Deep Learning Techniques: A Brief Review
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
Pyramid Diffusion Models for Low-light Image Enhancement
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
Gradient-Based Low-Light Image Enhancement [PDF]
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 +2 more
openaire +2 more sources
Invertible network for unpaired low-light image enhancement
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 +3 more
openaire +2 more sources
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
DCTE-LLIE: A Dual Color-and-Texture-Enhancement-Based Method for Low-Light Image Enhancement
The enhancement of images captured under low-light conditions plays a vitally important role in the area of image processing and can significantly affect the performance of following operations.
Hua Wang +3 more
doaj +1 more source
Low-Light Image Enhancement Using Photometric Alignment with Hierarchy Pyramid Network
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 +1 more source
DeepSelfie: Single-Shot Low-Light Enhancement for Selfies
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 +2 more
doaj +1 more source

