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

Images captured under poor lighting conditions often suffer from low brightness, low
contrast, color distortion, and noise. The function of low-light image enhancement is to …

Nighttime image dehazing is a challenging task due to the presence of multiple types of
adverse degrading effects including glow, haze, blur, noise, color distortion, and so on …

Visibility in hazy nighttime scenes is frequently reduced by multiple factors, including low
light, intense glow, light scattering, and the presence of multicolored light sources. Existing …

Most existing dehazing networks rely on synthetic hazy-clear image pairs for training, and
thus fail to work well in real-world scenes. In this paper, we deduce a reformulated …

The Remote Sensing (RS) field continuously grapples with the challenge of transforming
satellite data into actionable information. This ongoing issue results in an ever-growing …

Vision-dependent underwater vehicles are widely used in seabed resource exploration. The
visual perception system of underwater vehicles relies heavily on high-quality images for its …

Dehazing based on deep learning neural networks (CNNs) has achieved remarkable
results. However, the most existing dehazing CNNs perform well only on synthetic images …

Cooling fans are one of the critical components of air-forced dry-type transformers for
regulating internal temperatures. Therefore, effective malfunction detection is crucial to …

Remote sensing images are significantly degraded by bad weather conditions, such as haze
and sandstorms, which provide unhelpful support for valuable information extraction. Most …