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High-quality dehazing performance is highly dependent upon the accurate estimation of transmission map. In this work, the coarse estimation version is first obtained by weightedly fusing two different transmission maps, which are generated…

Computer Vision and Pattern Recognition · Computer Science 2019-02-20 Qiaoling Shu , Chuansheng Wu , Zhe Xiao , Ryan Wen Liu

Relying on the representation power of neural networks, most recent works have often neglected several factors involved in haze degradation, such as transmission (the amount of light reaching an observer from a scene over distance) and…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Eun Woo Im , Junsung Shin , Sungyong Baik , Tae Hyun Kim

Presence of haze in images obscures underlying information, which is undesirable in applications requiring accurate environment information. To recover such an image, a dehazing algorithm should localize and recover affected regions while…

Computer Vision and Pattern Recognition · Computer Science 2021-01-27 Pranjay Shyam , Kuk-Jin Yoon , Kyung-Soo Kim

Image-to-image translation based on generative adversarial network (GAN) has achieved state-of-the-art performance in various image restoration applications. Single image dehazing is a typical example, which aims to obtain the haze-free…

Image and Video Processing · Electrical Eng. & Systems 2022-10-11 Shichao Kan , Yue Zhang , Fanghui Zhang , Yigang Cen

This paper proposes a novel technique for single image dehazing. Most of the state-of-the-art methods for single image dehazing relies either on Dark Channel Prior (DCP) or on Color line. The proposed method combines the two different…

Computer Vision and Pattern Recognition · Computer Science 2019-06-11 Kushal Borkar , Snehasis Mukherjee

Images with haze of different varieties often pose a significant challenge to dehazing. Therefore, guidance by estimates of haze parameters related to the variety would be beneficial, and their progressive update jointly with haze reduction…

Computer Vision and Pattern Recognition · Computer Science 2024-10-30 Aupendu Kar , Sobhan Kanti Dhara , Debashis Sen , Prabir Kumar Biswas

How to effectively remove the noise while preserving the image structure features is a challenging issue in the field of image denoising. In recent years, fractional PDE based methods have attracted more and more research efforts due to the…

Numerical Analysis · Mathematics 2021-05-11 Maoyuan Xu , Xiaoping Xie

The recent physical model-free dehazing methods have achieved state-of-the-art performances. However, without the guidance of physical models, the performances degrade rapidly when applied to real scenarios due to the unavailable or…

Image and Video Processing · Electrical Eng. & Systems 2021-03-16 Yudong Liang , Bin Wang , Jiaying Liu , Deyu Li , Yuhua Qian , Wenqi Ren

Neural Radiance Field (NeRF) has received much attention in recent years due to the impressively high quality in 3D scene reconstruction and novel view synthesis. However, image degradation caused by the scattering of atmospheric light and…

Computer Vision and Pattern Recognition · Computer Science 2023-04-25 Tian Li , LU Li , Wei Wang , Zhangchi Feng

Particulate Matter (PM) is a form of air pollution that visually degrades urban scenery and is hazardous to human health and the environment. Current monitoring devices are limited in measuring average PM over large areas. Quantifying the…

Computer Vision and Pattern Recognition · Computer Science 2014-07-15 Tarek El-Gaaly , Joshua Gluckman

In recent years, partial differential equation (PDE) systems have been successfully applied to the binarization of text images, achieving promising results. Inspired by the DH model and incorporating a novel image modeling approach, this…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Youjin Liu , Yu Wang

Single image dehazing is an important low-level vision task with many applications. Early researches have investigated different kinds of visual priors to address this problem. However, they may fail when their assumptions are not valid on…

Computer Vision and Pattern Recognition · Computer Science 2018-08-01 Risheng Liu , Xin Fan , Minjun Hou , Zhiying Jiang , Zhongxuan Luo , Lei Zhang

Due to the domain gap between real-world and synthetic hazy images, current data-driven dehazing algorithms trained on synthetic datasets perform well on synthetic data but struggle to generalize to real-world scenarios. To address this…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Shijun Zhou , Xing Xie , Baojie Fan , Jiandong Tian

Haze removal is important for computational photography and computer vision applications. However, most of the existing methods for dehazing are designed for daytime images, and cannot always work well in the nighttime. Different from the…

Computer Vision and Pattern Recognition · Computer Science 2016-06-07 Jing Zhang , Yang Cao , Zengfu Wang

Haze removal has been a very challenging problem due to its ill-posedness, which is more ill-posed if the input data is only a single hazy image. In this paper, we present a new approach for removing haze from a single input image. The…

Computer Vision and Pattern Recognition · Computer Science 2016-01-25 Wei Wang , Chuanjiang He

In this paper, we propose an efficient visual transformer framework for ultra-high-definition (UHD) image dehazing that addresses the key challenges of slow training speed and high memory consumption for existing methods. Our approach…

Computer Vision and Pattern Recognition · Computer Science 2025-05-21 Pu Wang , Pengwen Dai , Chen Wu , Yeying Jin , Dianjie Lu , Guijuan Zhang , Youshan Zhang , Zhuoran Zheng

Haze limits the visibility of outdoor images, due to the existence of fog, smoke and dust in the atmosphere. Image dehazing methods try to recover haze-free image by removing the effect of haze from a given input image. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2018-12-05 Sanchayan Santra , Ranjan Mondal , Pranoy Panda , Nishant Mohanty , Shubham Bhuyan

Images captured under outdoor scenes usually suffer from low contrast and limited visibility due to suspended atmospheric particles, which directly affects the quality of photos. Despite numerous image dehazing methods have been proposed,…

Computer Vision and Pattern Recognition · Computer Science 2018-03-22 Chongyi Li , Jichang Guo , Fatih Porikli , Huazhu Fu , Yanwei Pang

We propose a new model, together with advanced optimization, to separate a thick scattering media layer from a single natural image. It is able to handle challenging underwater scenes and images taken in fog and sandstorm, both of which are…

Computer Vision and Pattern Recognition · Computer Science 2013-10-15 Qiong Yan , Li Xu , Jiaya Jia

Images captured in hazy weather generally suffer from quality degradation, and many dehazing methods have been developed to solve this problem. However, single image dehazing problem is still challenging due to its ill-posed nature. In this…

Computer Vision and Pattern Recognition · Computer Science 2024-08-13 Pengyang Ling , Huaian Chen , Xiao Tan , Yimeng Shan , Yi Jin