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A Progressive Single-Image Dehazing Network with Feedback Mechanism

Tisong Liang, Zhiwei Li, Yuanhong Ren, Qi Mao, Wuneng Zhou
2021 IEEE Access  
Moreover, we proposed an enhancement self-ensemble strategy to decrease the random error of the network to reconstruct clearer dehazing images.  ...  To resolve the above problem and reconstruct clearer and higher-quality dehazing images, we introduced our progressive feedback progressive network (PFBN) in recurrent structure ties with a feedback mechanism  ...  However, because the amount of useful information in a single hazy image is insufficient, dehazing algorithms are always considered ill-posed tasks [2] .  ... 
doi:10.1109/access.2021.3130468 fatcat:hduurjhh3jax7g4og3qq74ge2q

A Survey of Deep Learning-Based Image Restoration Methods for Enhancing Situational Awareness at Disaster Sites: The Cases of Rain, Snow and Haze

Sotiris Karavarsamis, Ioanna Gkika, Vasileios Gkitsas, Konstantinos Konstantoudakis, Dimitrios Zarpalas
2022 Sensors  
These image restoration methods are: (a) deraining; (b) desnowing; (c) dehazing ones.  ...  More specifically, the article surveys three families of image restoration methods serving the purpose of vision augmentation under adverse weather conditions.  ...  This model can progressively produce high quality deraining results, and it has a small set of parameters. It implements a novel residual-guide feature fusion network.  ... 
doi:10.3390/s22134707 pmid:35808203 pmcid:PMC9269588 fatcat:d34wmmvjznfcxfmh3vkj5qlk44

A Novel Encoder-Decoder Network with Guided Transmission Map for Single Image Dehazing [article]

Le-Anh Tran, Seokyong Moon, Dong-Chul Park
2022 arXiv   pre-print
A novel Encoder-Decoder Network with Guided Transmission Map (EDN-GTM) for single image dehazing scheme is proposed in this paper.  ...  dehazing performance.  ...  Numerous single image dehazing approaches have been proposed in attempt to enhance the visibility of hazy images and some of them have achieved significant progress.  ... 
arXiv:2202.04757v1 fatcat:pnphrhgdqfavnihulxf367ma3i

Progressive Depth Learning for Single Image Dehazing [article]

Yudong Liang, Bin Wang, Jiaying Liu, Deyu Li, Sanping Zhou, Wenqi Ren
2021 arXiv   pre-print
The image depth and transmission map are progressively refined to better restore the dehazed image.  ...  In this paper, a deep end-to-end model that iteratively estimates image depths and transmission maps is proposed to perform an effective depth prediction for hazy images and improve the dehazing performance  ...  [16] simultaneously performed the stereo matching and image dehazing in a feature fusion and multitask learning manner, which implicitly models the inner relationship between depth and transmission  ... 
arXiv:2102.10514v1 fatcat:f22dxkhkszdo5mn3w3ibwqo3eq

Joint image dehazing and super-resolution: closed shared source residual attention fusion network

Zhuoyuan Yang, Da Pan, Ping Shi
2021 IEEE Access  
Specifically, a shared source attention fusion (SAF) module is presented to fuse high-frequency information of different level features using shared source skip connections more effectively, which filters  ...  Therefore, it is a new trend to join the image dehazing and image super-resolution tasks.  ...  , which accumulates self-correcting features from each upsampling stage to generate SR images.  ... 
doi:10.1109/access.2021.3100328 fatcat:vog3icotnrfe7dbw5zj3n7fjua

Image Dehazing Based on Local and Non-Local Features

Qingliang Jiao, Ming Liu, Bu Ning, Fengfeng Zhao, Liquan Dong, Lingqin Kong, Mei Hui, Yuejin Zhao
2022 Fractal and Fractional  
and the proposed data-driven regularization terms are adopted to extract the local and non-local features of an image.  ...  Image dehazing is a traditional task, yet it still presents arduous problems, especially in the removal of haze from the texture and edge information of an image.  ...  Based on the guide filter, the weighted guided image filter [6] , the gradient-domain guided image filter [7] , and the anisotropic guided filtering method [8] have been widely employed in image dehazing  ... 
doi:10.3390/fractalfract6050262 fatcat:u2d5gqij7zev7dqxhifvo4witi

Snow Mask Guided Adaptive Residual Network for Image Snow Removal [article]

Bodong Cheng, Juncheng Li, Ying Chen, Shuyi Zhang, Tieyong Zeng
2022 arXiv   pre-print
Finally, an efficient Reconstruct-Net is used to remove the veiling effect and correct the image to reconstruct the final snow-free image.  ...  Firstly, we build a Mask-Net with Self-pixel Attention (SA) and Cross-pixel Attention (CA) to capture the features of snowflakes and accurately localized the location of the snow, thus predicting an accurate  ...  [22] analyzed a large number of haze-free images and proposed a well-known image dehazing algorithm guided by dark channel priors.  ... 
arXiv:2207.04754v1 fatcat:72ipvrlk6rdarcmg672ruuu4zm

Gated Fusion Network for Degraded Image Super Resolution [article]

Xinyi Zhang, Hang Dong, Zhe Hu, Wei-Sheng Lai, Fei Wang, Ming-Hsuan Yang
2020 arXiv   pre-print
The base features contain local and global information of the input image. On the other hand, the recovered features focus on the degraded regions and are used to remove the degradation.  ...  Single image super resolution aims to enhance image quality with respect to spatial content, which is a fundamental task in computer vision.  ...  . , N is used as the base features in the next block. Figure 3 shows the proposed recursive fusion process.  ... 
arXiv:2003.00893v2 fatcat:wslyimhivzh6pphadcmuxuuzsm

Regional Atmospheric Light Optimisation Algorithm for Heterogeneous Image Dehazing

Haoqiang Wu, Yiran Fu, Quanxing Zha, Aidong Chen, Hongyuan Jing, Yi-Zhang Jiang
2021 Scientific Programming  
It often produces an image with low contrast and low scene brightness, which is difficult to use in other image-based applications.  ...  The dark channel prior dehazing algorithm will cause the brightness of the image to decrease and sometimes introduce halos in the sky area.  ...  [28] proposed an end-to-end feature fusion dehazing network. is network structure can adaptively learn different weights of different-level feature information. e results show significant dominance  ... 
doi:10.1155/2021/3377905 fatcat:kt4oxps54zedfhz7retouglet4

An improved algorithm using weighted guided coefficient and union self‐adaptive image enhancement for single image haze removal

Guangbin Zhou, Lifeng He, Yong Qi, Meimei Yang, Xiao Zhao, Yuyan Chao
2021 IET Image Processing  
This paper proposes an improved algorithm for single-image haze removal based on dark channel prior with weighted guided coefficient and union self-adaptive image enhancement.  ...  Existing dehazing algorithms, such as dark channel prior (DCP) and colour attenuation prior (CAP), have made great progress and are highly effective.  ...  The proposed algorithm solves this problem by using a union self-adaptive image enhancement model.  ... 
doi:10.1049/ipr2.12255 fatcat:bjn5myp655bczcznkqqsyw5sz4

Table of contents

2020 IEEE Transactions on Image Processing  
X. 2653 Semi-Supervised Image Dehazing .................. L.Li, Y. Dong, W. Ren, J. Pan, C. Gao, N. Sang, and M.-H. Yang 2766 Deep Guided Learning for Fast Multi-Exposure Image Fusion ...  ...  Processing of Images and VideoUnsupervised Single Image Dehazing Using Dark Channel Prior Loss .........  ... 
doi:10.1109/tip.2019.2940373 fatcat:i7hktzn4wrfz5dhq7hj75u6esa

Learning Deep Interleaved Networks with Asymmetric Co-Attention for Image Restoration [article]

Feng Li, Runmin Cong, Huihui Bai, Yifan He, Yao Zhao, Ce Zhu
2020 arXiv   pre-print
Recently, convolutional neural network (CNN) has demonstrated significant success for image restoration (IR) tasks (e.g., image super-resolution, image deblurring, rain streak removal, and dehazing).  ...  In this way, the shallow information can guide deep representative features prediction to enhance the feature expression ability.  ...  Study of Feature Fusion Strategies In DIN, any feature fusion operation can be used at the interleaved nodes within the proposed IMBF.  ... 
arXiv:2010.15689v1 fatcat:xkq6qepctfhrpog73mca33jh74

2021 Index IEEE Transactions on Image Processing Vol. 30

2021 IEEE Transactions on Image Processing  
Nan, Z., +, TIP 2021 8293-8305 Progressive Self-Guided Loss for Salient Object Detection.  ...  ., +, TIP 2021 8968-8982 Atmospheric modeling IDRLP: Image Dehazing Using Region Line Prior.  ... 
doi:10.1109/tip.2022.3142569 fatcat:z26yhwuecbgrnb2czhwjlf73qu

Gradient Information Guided Deraining with A Novel Network and Adversarial Training [article]

Yinglong Wang, Haokui Zhang, Yu Liu, Qinfeng Shi, Bing Zeng
2019 arXiv   pre-print
Specifically, a modified ResNet-18 which extracts the deep features of rainy images and a revised ASPP structure which adapts to the various shapes and sizes of rain streaks are composed together to form  ...  In recent years, deep learning based methods have made significant progress in rain-removing.  ...  Finally, the fusion module acting as a decoder fuses the multi-scale feature f 2 and generates deraining result d.  ... 
arXiv:1910.03839v1 fatcat:ebe7f6xzundq5gyrzz2u4n6geu

Learning Transmission Filtering Network for Image-Based Pm2.5 Estimation

Yinghong Liao, Bin Qiu, Zhuo Su, Ruomei Wang, Xiangjian He
2019 2019 IEEE International Conference on Multimedia and Expo (ICME)  
Experimental results prove that our model performs favorably against the state-of-the-art dehazing methods in a variety of hazy scenes.  ...  Moreover, we introduce the attention mechanism to the network architecture for more efficient feature extraction and smoothing effects in the transmission estimation.  ...  Very recently, Ren et al. devised GFN [4] that could produce a hazy-free image via the fusion of effective dehazed patches from three feature maps. And Liu et al.  ... 
doi:10.1109/icme.2019.00054 dblp:conf/icmcs/LiaoQSWH19 fatcat:xgwotiwmofd4dho6xg43uw7g4u
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