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Related papers: Single Image Dehazing Using Scene Depth Ordering

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Underwater images suffer from extremely unfavourable conditions. Light is heavily attenuated and scattered. Attenuation creates change in hue, scattering causes so called veiling light. General state of the art methods for enhancing image…

Computer Vision and Pattern Recognition · Computer Science 2018-07-12 Tomasz Łuczyński , Andreas Birk

Image dehazing deals with the removal of undesired loss of visibility in outdoor images due to the presence of fog. Retinex is a color vision model mimicking the ability of the Human Visual System to robustly discount varying illuminations…

Computer Vision and Pattern Recognition · Computer Science 2018-04-09 Adrian Galdran , Aitor Alvarez-Gila , Alessandro Bria , Javier Vazquez-Corral , Marcelo Bertalmio

Hazy images reduce the visibility of the image content, and haze will lead to failure in handling subsequent computer vision tasks. In this paper, we address the problem of image dehazing by proposing a dehazing network named T-Net, which…

Computer Vision and Pattern Recognition · Computer Science 2021-06-08 Lirong Zheng , Yanshan Li , Kaihao Zhang , Wenhan Luo

Existing methods have achieved remarkable performance in image dehazing, particularly on synthetic datasets. However, they often struggle with real-world hazy images due to domain shift, limiting their practical applicability. This paper…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Ruiyi Wang , Wenhao Li , Xiaohong Liu , Chunyi Li , Zicheng Zhang , Xiongkuo Min , Guangtao Zhai

This report presents the results of a multi-scale wavelet based scheme for single image de-hazing and underwater image enhancement. The scheme is fast and highly localized in addition to global enhancement of hazy images. A PDE-based…

Computer Vision and Pattern Recognition · Computer Science 2021-12-01 Uche A. Nnolim

Considering the ill-posed nature, contrastive regularization has been developed for single image dehazing, introducing the information from negative images as a lower bound. However, the contrastive samples are nonconsensual, as the…

Computer Vision and Pattern Recognition · Computer Science 2023-06-02 Yu Zheng , Jiahui Zhan , Shengfeng He , Junyu Dong , Yong Du

In current practice, scene survey is carried out by workers using total stations. The method has high accuracy, but it incurs high costs if continuous monitoring is needed. Techniques based on photogrammetry, with the relatively cheaper…

Computer Vision and Pattern Recognition · Computer Science 2021-11-11 Kwok-Leung Chan , Liping Li , Arthur Wing-Tak Leung , Ho-Yin Chan

Single-image dehazing is an important topic in remote sensing applications, enhancing the quality of acquired images and increasing object detection precision. However, the reliability of such structures has not been sufficiently analyzed,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-28 Vlad Vasilescu , Ana Neacsu , Daniela Faur

To solve the issue of video dehazing, there are two main tasks to attain: how to align adjacent frames to the reference frame; how to restore the reference frame. Some papers adopt explicit approaches (e.g., the Markov random field, optical…

Computer Vision and Pattern Recognition · Computer Science 2021-07-19 Runde Li

Infrared and visible (IR-VIS) image fusion has gained significant attention for its broad application value. However, existing methods often neglect the complementary role of infrared image in restoring visible image features under hazy…

Computer Vision and Pattern Recognition · Computer Science 2026-01-12 Huafeng Li , Jiaqi Fang , Yafei Zhang , Yu Liu

We estimate scene depth from a single defocus-blurred image using the dark channel as a complementary cue, leveraging its ability to capture local statistics and scene structure. Traditional depth-from-defocus (DFD) methods use multiple…

Computer Vision and Pattern Recognition · Computer Science 2025-06-26 Moushumi Medhi , Rajiv Ranjan Sahay

We propose an enhanced multi-scale network, dubbed GridDehazeNet+, for single image dehazing. The proposed dehazing method does not rely on the Atmosphere Scattering Model (ASM), and an explanation as to why it is not necessarily performing…

Computer Vision and Pattern Recognition · Computer Science 2021-12-01 Xiaohong Liu , Zhihao Shi , Zijun Wu , Jun Chen

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

Unpaired image dehazing (UID) holds significant research importance due to the challenges in acquiring haze/clear image pairs with identical backgrounds. This paper proposes a novel method for UID named Orthogonal Decoupling Contrastive…

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

Existing dehazing methods deal with real-world haze images with difficulty, especially scenes with thick haze. One of the main reasons is the lack of real-world paired data and robust priors. To avoid the costly collection of paired hazy…

Computer Vision and Pattern Recognition · Computer Science 2025-08-18 Bing Liu , Le Wang , Mingming Liu , Hao Liu , Rui Yao , Yong Zhou , Peng Liu , Tongqiang Xia

Shadows often create unwanted artifacts in photographs, and removing them can be very challenging. Previous shadow removal methods often produce de-shadowed regions that are visually inconsistent with the rest of the image. In this work we…

Computer Vision and Pattern Recognition · Computer Science 2016-03-22 Liqian Ma , Jue Wang , Eli Shechtman , Kalyan Sunkavalli , Shimin Hu

Just like many other topics in computer vision, image classification has achieved significant progress recently by using deep-learning neural networks, especially the Convolutional Neural Networks (CNN). Most of the existing works are…

Computer Vision and Pattern Recognition · Computer Science 2018-10-15 Yanting Pei , Yaping Huang , Qi Zou , Hao Zang , Xingyuan Zhang , Song Wang

The goal of single-image deraining is to restore the rain-free background scenes of an image degraded by rain streaks and rain accumulation. The early single-image deraining methods employ a cost function, where various priors are developed…

Image and Video Processing · Electrical Eng. & Systems 2019-12-30 Wenhan Yang , Robby T. Tan , Shiqi Wang , Yuming Fang , Jiaying Liu

Hazy images are often subject to color distortion, blurring, and other visible quality degradation. Some existing CNN-based methods have great performance on removing homogeneous haze, but they are not robust in non-homogeneous case. The…

Image and Video Processing · Electrical Eng. & Systems 2021-06-22 Minghan Fu , Huan Liu , Yankun Yu , Jun Chen , Keyan Wang

Dehazing is a technique in computer vision for enhancing the visual quality of images captured in cloudy or foggy conditions. Dehazing helps to recover clear, high-quality images from haze-affected remote sensing data. In this study, we…

Computer Vision and Pattern Recognition · Computer Science 2026-04-21 Tejeswar Pokuri , Shivarth Rai
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