Images acquired in poor weather conditions (haze, fog, smog, mist, etc.) are often severely
degraded. In the atmosphere, there exists two types of particles: dry particles (dust, smoke …

Recent progress on Transformers and multi-layer perceptron (MLP) models provide new
network architectural designs for computer vision tasks. Although these models proved to be …

Haze is a poor-quality state described by the opalescent appearance of the atmosphere
which reduces the visibility. It is caused by high concentrations of atmospheric air pollutants …

Despite artificial intelligence (AI)'s significant growth, its “black box” nature creates
challenges in generating adequate trust. Thus, it is seldom utilized as a standalone unit in …

Nowadays, researchers use vision-based measurement tools to record, detect, and monitor
an atmospheric phenomenon called haze. It impedes the proper functioning of many …

Overcoming the link blockage challenges is essential for enhancing the reliability and
latency of millimeter wave (mmWave) and sub-terahertz (sub-THz) communication networks …

In this paper, we propose a novel method to address the nighttime single image dehazing
problem. Estimation of the ambient illumination map and transmission map are the key steps …

Adverse weather conditions can severely reduce the image quality captured by outdoor
imaging devices. However, most existing image restoration algorithms are designed for …

For the last two decades, image processing techniques have been used frequently in
computer vision applications. The most challenging task in image processing is restoring …

Image dehazing on a hazy image aims to remove the haze and make the image scene clear,
which attracts more and more research interests in recent years. Most existing image …