With the development of convolutional neural networks, hundreds of deep learning–based
dehazing methods have been proposed. In this article, we provide a comprehensive survey …

To overcome the overfitting issue of dehazing models trained on synthetic hazy-clean image
pairs, many recent methods attempted to improve models' generalization ability by training …

The Internet of Things (IoT) has recently emerged as a revolutionary communication
paradigm where a large number of objects and devices are closely interconnected to enable …

The presence of non-homogeneous haze can cause scene blurring, color distortion, low
contrast, and other degradations that obscure texture details. Existing homogeneous …

Because pixel values of foggy images are irregularly higher than those of images captured
in normal weather (clear images), it is difficult to extract and express their texture. No method …

Remote sensing image dehazing is of great scientific interest and application value in both
military and civil fields. In this article, we propose an enhanced attention-guide generative …

Images captured in hazy environments need to be processed to increase their contrast and
colour integrity. Dehazing, sometimes referred to as haze removal is an important pre …

Image restoration under hazy weather condition, which is called single image dehazing, has
been of significant interest for various computer vision applications. In recent years, deep …

Adverse weather conditions such as fog, haze, snow, mist and glare create visibility
problems for applications of autonomous vehicles. To ensure safe and smooth operations in …

Haze usually causes severe interference to image visibility. Such degradation on images
troubles both human observers and computer vision systems. To seek high-quality images …