Image restoration aims to reconstruct a high-quality image from a degraded low-quality
observation. Recently, Transformer models have achieved promising performance on image …

Image restoration aims to reconstruct a latent high-quality image from a degraded
observation. Recently, the usage of Transformer has significantly advanced the state-of-the …

Image restoration is the process of recovering a clean image from a degraded observation.
In order to achieve this, it is essential to refine features at multiple scales. This paper …

In real-world scenarios, the haze presents diversity and complexity. However, current
dehazing researches usually focus solely on specific categories or the removal of common …

Under hazy weather condition, images captured by electronic imaging devices frequently
encounter a number of issues, such as blurring of image details and the poorly defined …

Deep learning (DL) has recently shown superior performance for single-image dehazing.
Most deep dehazing networks either estimate the parameters of the atmospheric scattering …

Single image dehazing has been actively studied to overcome the quality degradation of
hazy images. Most of the existing methods take model-based approaches and the existing …

The use of a single image restoration framework to achieve multi-task image restoration has
garnered significant attention from researchers. However, several practical challenges …

Dehazing real-world hazy images is challenging due to the complexity of natural haze,
varying haze conditions, details preservation, and the risk of overexposure. Existing …

Owing to the heterogeneous spatial distribution and non-uniform morphological
characteristics of haze in remote sensing images (RSIs), conventional dehazing algorithms …