Images captured in weak illumination conditions could seriously degrade the image quality.
Solving a series of degradation of low-light images can effectively improve the visual quality …

Images captured under low-light conditions are typically prone to undesirable visual
phenomena, particularly color distortion and additive noise, that impede the aesthetics and …

Due to the wide dynamic range in real low-light scenes, there will be large differences in the
degree of contrast degradation and detail blurring of captured images, making it difficult for …

Pre-processing techniques such as low-light image improvement have a wide variety of
practical uses. Enhancing optical acuity and the caliber of photos taken in low-light are the …

Image dehazing is an important technique aimed at eliminating the haze in the atmosphere
to enhance the image's visual quality. There are many applications where it has been used …

In low-light environments, the amount of light captured by the camera sensor is reduced,
resulting in lower image brightness. This makes it difficult to recognize or completely lose …

The research presents a comprehensive exploration of the topic of image enhancement
using convolutional neural networks (CNN). The research goes deeper into the advanced …

Digital camera sensors may struggle to capture images in low-light environments, resulting
in lower brightness and contrast levels, color degradation, undesirable characteristics, and …

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 …

Images captured in low light conditions suffer from low visibility, blurred details and strong
noise, resulting in unpleasant visual appearance and poor performance of high level visual …