Existing dehazing approaches struggle to process real-world hazy images owing to the lack
of paired real data and robust priors. In this work, we present a new paradigm for real image …

Image dehazing is always a hot topic in the field of computer vision since haze has
significant impact on the imaging quality of camera. Therefore, many image dehazing …

Image restoration under multiple adverse weather conditions aims to remove weather-
related artifacts by using the single set of network parameters. In this paper, we find that …

Transformer-based approaches have achieved promising performance in image restoration
tasks given their ability to model long-range dependencies which is crucial for recovering …

Saturation information in hazy images is conducive to effective haze removal, However,
existing saturation-based dehazing methods just focus on the saturation value of each pixel …

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 …

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 …

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 …

Few existing image defogging or dehazing methods consider dense and non-uniform
particle distributions, which usually happen in smoke, dust and fog. Dealing with these …

Recently, CycleGAN-based methods have been widely applied to the unsupervised image
dehazing and achieved significant results. However, most existing CycleGAN-based …