Currently, most single image dehazing models cannot run an ultra-high-resolution (UHD) with a GPU shader in real-time. To address the problem, we introduce principle of infinite approximation Taylor's theorem Laplace pyramid pattern to build model which is capable handling 4K hazy images The N branch networks network correspond constraint terms theorem. Low-order polynomials reconstruct low-fre...

To solve the issue of video dehazing, there are two main tasks to attain: how align adjacent frames reference frame; restore frame. Some papers adopt explicit approaches (e.g., Markov random field, optical flow, deformable convolution, 3D convolution) neighboring with frame in feature space or image space, then various restoration methods used achieve final dehazing results. In this paper, we p...

Recently, most dehazed image quality assessment (DQA) methods mainly focus on the estimation of remaining haze, omitting impact distortions from side effect dehazing algorithms, which lead to their limited performance. Addressing this problem, we proposed a learning both Visibility and Distortion Aware features no-reference (NR) Dehazed Quality Assessment method (VDA-DQA). aware are exploited c...

Single image dehazing is a challenging ill-posed problem that has drawn significant attention in the last few years. Recently, convolutional neural networks have achieved great success dehazing. However, it still difficult for these increasingly complex models to recover accurate details from hazy image. In this paper, we pay feature extraction and utilization of input itself. To achieve this, ...

Single-image haze removal is a long-standing hurdle for computer vision applications. Several works have been focused on transferring advances from image classification, detection, and segmentation to the niche of dehazing, primarily focusing contrastive learning knowledge distillation. However, these approaches prove computationally expensive, raising concern regarding their applicability on-t...

Abstract Image dehazing is an increasingly widespread approach to address the degradation of images natural environment by low-visibility weather, dust and other phenomena. Advances in autonomous systems platforms have increased need for low-complexity, high-performing techniques. However, while recent learning-based image approaches significantly performance, this has often been at expense com...