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
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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
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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
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An Empirical Study on Retinex Methods for Low-Light Image Enhancement [PDF]
Remote Sensing, 2022 A key part of interpreting, visualizing, and monitoring the surface conditions of remote-sensing images is enhancing the quality of low-light images.
Muhammad Tahir Rasheed +4 more
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Retinex-Based Relighting for Night Photography
Applied Sciences, 2023 The lighting up of buildings is one form of entertainment that makes a city more colorful, and photographers sometimes change this lighting using photo-editing applications.
Sou Oishi, Norishige Fukushima
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DCD-Net: Decoupling-Centric Decomposition Network for Low-Light Image Enhancement [PDF]
SensorsThis paper presents a Decoupling-Centric Decomposition network for Low-Light Image Enhancement (DCD-Net). The DCDNet addresses two key challenges: (1) existing methods center on how to design the enhancement network and ignore the decomposition network’s
Wei Wang +3 more
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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
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A TV Bregman iterative model of Retinex theory
Inverse Problems and Imaging, 2012 A feature of the human visual system (HVS) is color constancy, namely, the ability to determine the color under varying illumination conditions. Retinex theory, formulated by Edwin H. Land, aimed to simulate and explain how the HVS perceives color.
Stanley Osher
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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
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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
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