NTIRE 2024 dense and non-homogeneous dehazing challenge report
This study examines the results of the NTIRE 2024 Challenge on Dense and Non-
Homogeneous Dehazing. Innovative methods were introduced and tested using a new …
Homogeneous Dehazing. Innovative methods were introduced and tested using a new …
A comprehensive survey on image dehazing for different atmospheric scattering models
S An, X Huang, L Cao, L Wang - Multimedia Tools and Applications, 2024 - Springer
Image dehazing techniques are widely used in complex outdoor environments and are
commonly categorized based on learning mechanisms. However, the imaging mechanism …
commonly categorized based on learning mechanisms. However, the imaging mechanism …
Graph Convolutional Network for Image Restoration: A Survey
Image restoration technology is a crucial field in image processing and is extensively utilized
across various domains. Recently, with advancements in graph convolutional network …
across various domains. Recently, with advancements in graph convolutional network …
[HTML][HTML] Densely integrated multi-branch attentive net for image dehazing
P Zong, Z Hua, J Li - Ain Shams Engineering Journal, 2024 - Elsevier
Single image dehazing is a fundamental but challenging task in image processing. Various
deep learning-based methods have achieved great dehazing performance. However, there …
deep learning-based methods have achieved great dehazing performance. However, there …
RepDehazeNet: Dual subnets image dehazing network based on structural re-parameterization
X Luo, H Zhong, J Lu, C Meng, X Han - Computers & Graphics, 2024 - Elsevier
In recent times, there has been notable and swift advancement in the field of image
dehazing. Several deep learning techniques have demonstrated remarkable proficiency in …
dehazing. Several deep learning techniques have demonstrated remarkable proficiency in …
LBP-based multi-scale feature fusion enhanced dehazing networks
X Zhang, Y Li, J Li, Z Hua - Multimedia Tools and Applications, 2024 - Springer
Image dehazing is a prior process to perform advanced computer vision tasks such as
certain target detection, and the degree of haze residue directly determines the performance …
certain target detection, and the degree of haze residue directly determines the performance …
LRB-T: local reasoning back-projection transformer for the removal of bad weather effects in images
P Wang, H Zhu, H Zhang, S Yang - Neural Computing and Applications, 2024 - Springer
In computer vision, transformers have shown increasing effectiveness for high-level vision
tasks. To further cope with low-level vision tasks, we propose a general framework, namely …
tasks. To further cope with low-level vision tasks, we propose a general framework, namely …
Multi-scale recurrent attention gated fusion network for single image dehazing
X Zhang, S Yang, Q Zhang, F Yuan - Journal of Visual Communication and …, 2024 - Elsevier
The purpose of single image dehazing is to eliminate the bad influence of haze on images,
so as to maintain more scene information of images. In recent years, the convolutional …
so as to maintain more scene information of images. In recent years, the convolutional …
Improved image dehazing model with color correction transform-based dark channel prior
The precise identification and positioning of objects require the restoration of hazy images.
This paper proposes the implementation of Color Correction Transform based Dark Channel …
This paper proposes the implementation of Color Correction Transform based Dark Channel …
[PDF][PDF] 基于双流Transformer 的单幅图像去雾方法
李岸然， 方阳阳， 程慧杰， 张申申， 阎金强， 于腾… - 计算机与现代化, 2024 - cam.org.cn
基于深度学习的编码器-解码器网络在图像去雾问题上取得了优异的表现. 然而,
这些学习方法通常仅依赖于合成数据集进行模型训练, 忽视了有关模糊图像的先验知识 …
这些学习方法通常仅依赖于合成数据集进行模型训练, 忽视了有关模糊图像的先验知识 …