EIEN: Endoscopic Image Enhancement Network Based on Retinex Theory [PDF]
Sensors, 2022 In recent years, deep convolutional neural network (CNN)-based image enhancement has shown outstanding performance. However, due to the problems of uneven illumination and low contrast existing in endoscopic images, the implementation of medical ...
Ziheng An +6 more
doaj +7 more sources
Image Restoration via Low-Illumination to Normal-Illumination Networks Based on Retinex Theory [PDF]
Sensors, 2023 Under low-illumination conditions, the quality of the images collected by the sensor is significantly impacted, and the images have visual problems such as noise, artifacts, and brightness reduction.
Chaoran Wen +4 more
doaj +5 more sources
ILR-Net: Low-light image enhancement network based on the combination of iterative learning mechanism and Retinex theory. [PDF]
PLoS ONEImages captured in nighttime or low-light environments are often affected by external factors such as noise and lighting. Aiming at the existing image enhancement algorithms tend to overly focus on increasing brightness, while neglecting the enhancement ...
Mohan Yin, Jianbai Yang
doaj +3 more sources
Low-Light Image Enhancement Method Based on Retinex Theory by Improving Illumination Map
Applied Sciences, 2022 Recently, low-light image enhancement has attracted much attention. However, some problems still exist. For instance, sometimes dark regions are not fully improved, but bright regions near the light source or auxiliary light source are overexposed.
Xinxin Pan +5 more
doaj +4 more sources
Improved Retinex-Theory-Based Low-Light Image Enhancement Algorithm
Applied Sciences, 2023 Researchers working on image processing have had a hard time handling low-light images due to their low contrast, noise, and brightness. This paper presents an improved method that uses the Retinex theory to enhance low-light images, with a network model
Jiarui Wang +3 more
doaj +4 more sources
Low-Light Image Enhancement Algorithm Based on Deep Learning and Retinex Theory
Applied Sciences, 2023 To address the challenges of low-light images, such as low brightness, poor contrast, and high noise, a network model based on deep learning and Retinex theory is proposed.
Chenyu Lei, Qichuan Tian
doaj +4 more sources
Lightness and Retinex Theory [PDF]
Journal of the Optical Society of America, 1971 Sensations of color show a strong correlation with reflectance, even though the amount of visible light reaching the eye depends on the product of reflectance and illumination. The visual system must achieve this remarkable result by a scheme that does not measure flux. Such a scheme is described as the basis of retinex theory. This theory assumes that
E H, Land, J J, McCann
openaire +3 more sources
A depth iterative illumination estimation network for low-light image enhancement based on retinex theory. [PDF]
Sci Rep, 2023 Existing low-light image enhancement techniques face challenges in achieving high visual quality and computational efficiency, as well as in effectively removing noise and adjusting illumination in extremely dark scenes.
Chen Y, Wen C, Liu W, He W.
europepmc +2 more sources
Non-Uniform-Illumination Image Enhancement Algorithm Based on Retinex Theory
Applied Sciences, 2023 To address the issues of fuzzy scene details, reduced definition, and poor visibility in images captured under non-uniform lighting conditions, this paper presents an algorithm for effectively enhancing such images.
Xiu Ji +3 more
doaj +2 more sources
Applied SciencesLow-illumination images can seriously affect or even limit the performance of the human eye or a computer vision system, making image enhancement processing necessary.
Haixia Mao +3 more
doaj +2 more sources