In recent years, learning-based single image dehazing networks have been
comprehensively developed. However, performance improvement is limited due to domain …

Despite the recent progress in image dehazing, the task remains tremendous challenging.
To improve the performance of haze removal, we propose a scheme for haze removal based …

Recently, convolutional neural networks (CNNs) have achieved great improvements in
single image dehazing and attained much attention in research. Most existing learning …

Image dehazing is a critical image pre-processing task to estimate the haze-free images
corresponding to the input hazy images. Despite the recent advances, the task of image …

Single image dehazing is an important problem as the existence of haze degrades the
quality of the image and hinders most high-level computer vision tasks. Previous methods …

Single image dehazing has great significance in computer vision. In this paper, we propose
a novel unsupervised Dark Channel Attention optimized CycleGAN (DCA-CycleGAN) to …

In this paper, we propose a novel image dehazing method. Typical deep learning models for
dehazing are trained on paired synthetic indoor dataset. Therefore, these models may be …

Owing to the fast developments of economics, a lot of devices and objects have been
connected and have formed the Internet of Things (IoT). Visual sensors have been applied …

Convolutional neural networks (CNNs) have attracted much research attention and
achieved great improvements in single-image dehazing. However, previous learning-based …

Single image dehazing is a challenging vision task that recovers haze-free images from
observed hazy images. Recently, numerous learning-based dehazing methods have been …