Results 1 to 10 of about 819,645 (117)
Decoupled Low-Light Image Enhancement [PDF]
ACM Transactions on Multimedia Computing, Communications, and Applications, 2022 The visual quality of photographs taken under imperfect lightness conditions can be degenerated by multiple factors, e.g., low lightness, imaging noise, color distortion, and so on. Current low-light image enhancement models focus on the improvement of low lightness only, or simply deal with all the degeneration factors as a whole, therefore leading to
Shijie Hao +3 more
openaire +2 more sources
A Survey of Deep Learning-Based Low-Light Image Enhancement [PDF]
Sensors, 2023 Zheng Liang, Weidong Zhang, Yukun Sun
exaly +2 more sources
Towards Low Light Enhancement With RAW Images [PDF]
IEEE Transactions on Image Processing, 2022 In this paper, we make the first benchmark effort to elaborate on the superiority of using RAW images in the low light enhancement and develop a novel alternative route to utilize RAW images in a more flexible and practical way. Inspired by a full consideration on the typical image processing pipeline, we are inspired to develop a new evaluation ...
Haofeng Huang +4 more
openaire +3 more sources
A survey on image enhancement for Low-light images
Heliyon, 2023 In real scenes, due to the problems of low light and unsuitable views, the images often exhibit a variety of degradations, such as low contrast, color distortion, and noise. These degradations affect not only visual effects but also computer vision tasks. This paper focuses on the combination of traditional algorithms and machine learning algorithms in
Jiawei Guo +4 more
openaire +3 more sources
Low-Light Hyperspectral Image Enhancement
IEEE Transactions on Geoscience and Remote Sensing, 2022 Due to inadequate energy captured by the hyperspectral camera sensor in poor illumination conditions, low-light hyperspectral images (HSIs) usually suffer from low visibility, spectral distortion, and various noises. A range of HSI restoration methods have been developed, yet their effectiveness in enhancing low-light HSIs is constrained.
Xuelong Li 0001 +2 more
openaire +2 more sources
Dynamic Low-Light Imaging with Quanta Image Sensors [PDF]
, 2020 Published in the 16th European Conference on Computer Vision (ECCV ...
Yiheng Chi +3 more
openaire +2 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 +4 more
openaire +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 +5 more
openaire +2 more sources
Adaptive Enhancement of Extreme Low-Light Images
, 2023 Existing methods for enhancing dark images captured in a very low-light environment assume that the intensity level of the optimal output image is known and already included in the training set. However, this assumption often does not hold, leading to output images that contain visual imperfections such as dark regions or low contrast.
Evgeny Hershkovitch Neiterman +2 more
openaire +2 more sources
Towards Robust Low Light Image Enhancement
CoRR, 2022 In this paper, we study the problem of making brighter images from dark images found in the wild. The images are dark because they are taken in dim environments. They suffer from color shifts caused by quantization and from sensor noise. We don't know the true camera reponse function for such images and they are not RAW.
Sara Aghajanzadeh, David A. Forsyth
openaire +2 more sources