Results 31 to 40 of about 739 (170)

Research on Multi-Scale Feature Fusion Dehazing Network Based on Feature Differences [PDF]

Jisuanji gongcheng
Haze, formed by the accumulation and concentration of atmospheric pollutants under meteorological conditions, such as temperature inversion, severely limits visibility.
LIU Yanhong, YANG Qiuxiang, HU Shuai
doaj   +1 more source

Fast Deep Multi-patch Hierarchical Network for Nonhomogeneous Image Dehazing

, 2020
Recently, CNN based end-to-end deep learning methods achieve superiority in Image Dehazing but they tend to fail drastically in Non-homogeneous dehazing.
Das, Sourya Dipta, Dutta, Saikat
core   +1 more source

Fusion-based Variational Image Dehazing [PDF]

IEEE Signal Processing Letters, 2016
We propose a novel image-dehazing technique based on the minimization of two energy functionals and a fusion scheme to combine the output of both optimizations. The proposed fusion-based variational image-dehazing (FVID) method is a spatially varying image enhancement process that first minimizes a previously proposed variational formulation that ...
Adrian Galdran, Javier Vazquez-Corral, David Pardo, Marcelo Bertalmio   +3 more
openaire   +3 more sources

Efficient Dehazing Method for Outdoor and Remote Sensing Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
As an atmospheric phenomenon, haze significantly reduces the visibility of outdoor and remote sensing images. As remote sensing and outdoor imaging have different mechanisms, existing dehazing methods are hard to be applied for both outdoor images and ...
Chenyang Li, Hang Yu, Suiping Zhou, Zhiheng Liu, Yuru Guo, Xiangjie Yin, Wenjie Zhang   +6 more
doaj   +1 more source

Learning of Image Dehazing Models for Segmentation Tasks

, 2019
To evaluate their performance, existing dehazing approaches generally rely on distance measures between the generated image and its corresponding ground truth.
berman, chen, fattal, goodfellow, he, johnson, ren, silberman, simonyan, yang   +9 more
core   +1 more source

Dense-HR-GAN: A High-Resolution GAN Model with Dense Connection for Image Dehazing in Icing Wind Tunnel Environment

Applied Sciences, 2023
To address the issue of blurred images generated during ice wind tunnel tests, we propose a high-resolution dense-connection GAN model, named Dense-HR-GAN.
Wenjun Zhou, Xinling Yang, Chenglin Zuo, Yifan Wang, Bo Peng   +4 more
doaj   +1 more source

A Ship Tracking and Speed Extraction Framework in Hazy Weather Based on Deep Learning

Journal of Marine Science and Engineering, 2023
Obtaining ship navigation information from maritime videos can significantly improve maritime supervision efficiency and enable timely safety warnings. Ship detection and tracking are essential technologies for mining video information.
Zhenzhen Zhou, Jiansen Zhao, Xinqiang Chen, Yanjun Chen   +3 more
doaj   +1 more source

Filmy Cloud Removal on Satellite Imagery with Multispectral Conditional Generative Adversarial Nets

, 2017
In this paper, we propose a method for cloud removal from visible light RGB satellite images by extending the conditional Generative Adversarial Networks (cGANs) from RGB images to multispectral images.
Enomoto, Kenji, Fukui, Hiroshi, Kawaguchi, Nobuo, Matsuoka, Masashi, Nakamura, Ryosuke, Sakurada, Ken, Wang, Weimin   +6 more
core   +1 more source

Nighttime Dehaze-Enhancement

, 2022
In this paper, we introduce a new computer vision task called nighttime dehaze-enhancement. This task aims to jointly perform dehazing and lightness enhancement. Our task fundamentally differs from nighttime dehazing -- our goal is to jointly dehaze and enhance scenes, while nighttime dehazing aims to dehaze scenes under a nighttime setting.
Baskar, Harshan, Chakravarthy, Anirudh S, Garg, Prateek, Goel, Divyam, Raj, Abhijith S, Kumar, Kshitij, Lakshya, Parvatham, Ravichandra, Sushant, V, Rout, Bijay Kumar   +9 more
openaire   +2 more sources

Semi‐supervised learning dehazing algorithm based on the OSV model

IET Image Processing, 2023
Despite the great progress that has been made in the task of single image dehazing, the results of the existing models in restoring image edge and texture information are still challenging.
Lijun Zhu, Weibo Wei, Zhenkuan Pan, Lianshun Ji, Jintao Song, Jinhan Li   +5 more
doaj   +1 more source