Images captured under poor illumination conditions often exhibit characteristics such as low
brightness, low contrast, a narrow gray range, and color distortion, as well as considerable …

Low-light image (LLI) enhancement is an important image processing task that aims at
improving the illumination of images taken under low-light conditions. Recently, a …

Retinex theory is developed mainly to decompose an image into the illumination and
reflectance components by analyzing local image derivatives. In this theory, larger …

Image captured under poor-illumination conditions often display attributes of having poor
contrasts, low brightness, a narrow gray range, colour distortions and considerable …

Abstract The Retinex Theory (RT) and its adaptations have gained significant popularity in
the field of image processing. Nevertheless, traditional Retinex algorithms are generally …

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 …

Low-light image (LLI) enhancement techniques have recently demonstrated remarkable
progress especially with the use of deep learning approaches. However, most existing …

Maritime images captured under low-light imaging condition easily suffer from low visibility
and unexpected noise, leading to negative effects on maritime traffic supervision and …

Images captured in low-light or underwater environments are often accompanied by
significant degradation, which can negatively impact the quality and performance of …

Liver cancer diagnosis requires preprocessing of images with preserved structural details. In
this study, a multi-level generative adversarial network (GAN) is proposed to enhance …