In the past decades, remote sensing (RS) data fusion has always been an active research
community. A large number of algorithms and models have been developed. Generative …

Abstract Single Image Super Resolution (SISR) is a process to obtain a high pixel density
and refined details from a low resolution (LR) image to get upscaled and sharper high …

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 …

Removing adverse weather conditions like rain, fog, and snow from images is an important
problem in many applications. Most methods proposed in the literature have been designed …

Deep learning-based methods have achieved remarkable performance for image dehazing.
However, previous studies are mostly focused on training models with synthetic hazy …

In this paper, we propose a Multi-Scale Boosted Dehazing Network with Dense Feature
Fusion based on the U-Net architecture. The proposed method is designed based on two …

Haze-free images are the prerequisites of many vision systems and algorithms, and thus
single image dehazing is of paramount importance in computer vision. In this field, prior …

Convolutional neural networks (CNNs) have achieved significant success in the single
image dehazing task. Unfortunately, most existing deep dehazing models have high …

Deep learning-based methods have achieved remarkable success in image restoration and
enhancement, but are they still competitive when there is a lack of paired training data? As …

Image dehazing using learning-based methods has achieved state-of-the-art performance in
recent years. However, most existing methods train a dehazing model on synthetic hazy …