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Recovering a clear image from a single hazy image is an open inverse problem. Although significant research progress has been made, most existing methods ignore the effect that downstream tasks play in promoting upstream dehazing. From the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-15 Yafei Zhang , Shen Zhou , Huafeng Li

Image restoration under adverse weather conditions refers to the process of removing degradation caused by weather particles while improving visual quality. Most existing deweathering methods rely on increasing the network scale and data…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Zihan Shen , Yu Xuan , Qingyu Yang

Despite the recent progress in image dehazing, several problems remain largely unsolved such as robustness for varying scenes, the visual quality of reconstructed images, and effectiveness and flexibility for applications. To tackle these…

Computer Vision and Pattern Recognition · Computer Science 2017-12-05 Chongyi Li , Jichang Guo , Fatih Porikli , Chunle Guo , Huzhu Fu , Xi Li

Recent advancements in unpaired dehazing, particularly those using GANs, show promising performance in processing real-world hazy images. However, these methods tend to face limitations due to the generator's limited transport mapping…

Computer Vision and Pattern Recognition · Computer Science 2025-07-15 Yunwei Lan , Zhigao Cui , Xin Luo , Chang Liu , Nian Wang , Menglin Zhang , Yanzhao Su , Dong Liu

Video dehazing aims to recover haze-free frames with high visibility and contrast. This paper presents a novel framework to effectively explore the physical haze priors and aggregate temporal information. Specifically, we design a…

Computer Vision and Pattern Recognition · Computer Science 2023-03-20 Jiaqi Xu , Xiaowei Hu , Lei Zhu , Qi Dou , Jifeng Dai , Yu Qiao , Pheng-Ann Heng

In recent years, single image dehazing models (SIDM) based on atmospheric scattering model (ASM) have achieved remarkable results. However, it is noted that ASM-based SIDM degrades its performance in dehazing real world hazy images due to…

Computer Vision and Pattern Recognition · Computer Science 2021-08-26 Cong Wang , Yan Huang , Yuexian Zou , Yong Xu

In real-world scenarios, image defogging is an inverse problem due to unknown scene depth, atmospheric scattering, and the common absence of ground truth . To resolve the issue, we propose a hybrid defogging model that integrates a…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Manish Kumar , Rajendra K. Ray

Image Dehazing (ID) aims to produce a clear image from an observation contaminated by haze. Current ID methods typically rely on carefully crafted priors or extensive haze-free ground truth, both of which are expensive or impractical to…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Zhang Wen , Jiangwei Xie , Dongdong Chen

Nighttime photography is severely degraded by light pollution induced by pervasive artificial lighting in urban environments. After long-range scattering and spatial diffusion, unwanted artificial light overwhelms natural night luminance,…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Hao Wang , Xiaolin Wu , Xi Zhang , Baoqing Sun

Learning-based real image dehazing methods have achieved notable progress, yet they still face adaptation challenges in diverse real haze scenes. These challenges mainly stem from the lack of effective unsupervised mechanisms for unlabeled…

Computer Vision and Pattern Recognition · Computer Science 2026-03-12 Yan Zhang , Long Ma , Yuxin Feng , Zhe Huang , Fan Zhou , Zhuo Su

The bilateral filter is a useful nonlinear filter which without smoothing edges, it does spatial averaging. In the literature, the effectiveness of this method for image denoising is shown. In this paper, an extension of this method is…

Computer Vision and Pattern Recognition · Computer Science 2017-02-07 Seyede Mahya Hazavei , Hamid Reza Shahdoosti

Currently, mobile and IoT devices are in dire need of a series of methods to enhance 4K images with limited resource expenditure. The absence of large-scale 4K benchmark datasets hampers progress in this area, especially for dehazing. The…

Computer Vision and Pattern Recognition · Computer Science 2023-03-29 Zhuoran Zheng , Xiuyi Jia

Underwater images are typically characterized by color cast, haze, blurring, and uneven illumination due to the selective absorption and scattering when light propagates through the water, which limits their practical applications.…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Yuemei Li , Guojia Hou , Peixian Zhuang , Zhenkuan Pan

Increasing the visibility of nighttime hazy images is challenging because of uneven illumination from active artificial light sources and haze absorbing/scattering. The absence of large-scale benchmark datasets hampers progress in this…

Computer Vision and Pattern Recognition · Computer Science 2020-10-20 Jing Zhang , Yang Cao , Zheng-Jun Zha , Dacheng Tao

Low-light hazy scenes commonly appear at dusk and early morning. The visual enhancement for low-light hazy images is an ill-posed problem. Even though numerous methods have been proposed for image dehazing and low-light enhancement…

Computer Vision and Pattern Recognition · Computer Science 2023-08-02 Chaoqun Zhuang , Yunfei Liu , Sijia Wen , Feng Lu

Adverse weather conditions often impair the quality of captured images, inevitably inducing cutting-edge object detection models for advanced driver assistance systems (ADAS) and autonomous driving. In this paper, we raise an intriguing…

Computer Vision and Pattern Recognition · Computer Science 2025-04-03 Yihua Fan , Yongzhen Wang , Mingqiang Wei , Fu Lee Wang , Haoran Xie

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

Image dehazing without paired haze-free images is of immense importance, as acquiring paired images often entails significant cost. However, we observe that previous unpaired image dehazing approaches tend to suffer from performance…

Image and Video Processing · Electrical Eng. & Systems 2020-07-13 Chen Liu , Jiaqi Fan , Guosheng Yin

We propose a novel method of efficient upsampling of a single natural image. Current methods for image upsampling tend to produce high-resolution images with either blurry salient edges, or loss of fine textural detail, or spurious noise…

Computer Vision and Pattern Recognition · Computer Science 2015-03-03 Chinmay Hegde , Oncel Tuzel , Fatih Porikli

In image dehazing task, haze density is a key feature and affects the performance of dehazing methods. However, some of the existing methods lack a comparative image to measure densities, and others create intermediate results but lack the…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Zhongze Wang , Haitao Zhao , Lujian Yao , Jingchao Peng , Kaijie Zhao