Results 31 to 40 of about 4,947 (184)

Survey of Transformer-Based Single Image Dehazing Methods [PDF]

Jisuanji kexue yu tansuo
As a fundamental computer vision task, image dehazing aims to preprocess degraded images by restoring color contrast and texture information to improve visibility and image quality, thereby the clear images can be recovered for subsequent high-level ...
ZHANG Kaili, WANG Anzhi, XIONG Yawei, LIU Yun
doaj   +1 more source

Satellite Image Dehazing

International Journal for Research in Applied Science and Engineering Technology, 2023
Abstract: The images captured during haze, murkiness and raw weather has serious degradation in them. Image dehazing of a single image is a problematic affair. While already-in-use systems depend on high-quality images, some Computer Vision applications, such self-driving cars and image restoration, typically use input from data that is of poor quality.
openaire   +1 more source

Multilevel Image Dehazing Algorithm Using Conditional Generative Adversarial Networks

IEEE Access, 2020
In recent years, the hazy weather in China occurs frequently, and image dehazing has gradually become a research hotspot. To improve the dehazing effect of the hazy images, this paper has proposed a multilevel image dehazing algorithm using conditional ...
Kailei Gan, Jieyu Zhao, Hao Chen
doaj   +1 more source

One-Sided Unsupervised Image Dehazing Network Based on Feature Fusion and Multi-Scale Skip Connection

Applied Sciences, 2022
Haze and mist caused by air quality, weather, and other factors can reduce the clarity and contrast of images captured by cameras, which limits the applications of automatic driving, satellite remote sensing, traffic monitoring, etc. Therefore, the study
Yuanbo Yang, Qunbo Lv, Baoyu Zhu, Xuefu Sui, Yu Zhang, Zheng Tan   +5 more
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Deep Learning-Enabled Variational Optimization Method for Image Dehazing in Maritime Intelligent Transportation Systems

Journal of Advanced Transportation, 2021
Image dehazing has become a fundamental problem of common concern in computer vision-driven maritime intelligent transportation systems (ITS). The purpose of image dehazing is to reconstruct the latent haze-free image from its observed hazy version.
Xianjun Hu, Jing Wang, Chunlei Zhang, Yishuo Tong   +3 more
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Image Dehazing Based on Improved Color Channel Transfer and Multiexposure Fusion

Advances in Multimedia, 2023
Image dehazing is one of the problems that need to be solved urgently in the field of computer vision. In recent years, more and more algorithms have been applied to image dehazing and achieved good results.
Shaojin Ma, Weiguo Pan, Hongzhe Liu, Songyin Dai, Bingxin Xu, Cheng Xu, Xuewei Li, Huaiguang Guan   +7 more
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A Model-Driven Deep Dehazing Approach by Learning Deep Priors

IEEE Access, 2021
Photos taken in hazy weather are usually covered with white masks and lose important details. Haze removal is a fundamental task and a prerequisite to many other vision tasks.
Dong Yang, Jian Sun
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Single image dehazing based on hazy features extraction and enhancement network

Journal of Measurement Science and Instrumentation, 2023
Convolutional neural network is developing rapidly in image processing. Most image dehazing algorithms only focus on dehazing but neglect the overall quality of dehazing image, which leads to problems such as loss of information blurred texture, etc.
ZHANG Jinlong, YANG Yan
doaj  

NTIRE 2020 Challenge on NonHomogeneous Dehazing

, 2020
This paper reviews the NTIRE 2020 Challenge on NonHomogeneous Dehazing of images (restoration of rich details in hazy image). We focus on the proposed solutions and their results evaluated on NH-Haze, a novel dataset consisting of 55 pairs of real haze ...
Ancuti, Codruta O., Ancuti, Cosmin, Chang, Jerome, Chang, Yu-Bang, Chao, Ju-Chin, Chen, Peng-Wen, Chen, Siyi, Cherukuri, Venkateswararao, Chuang, Shiue-Yuan, Das, Sourya Dipta, de Dravo, Vincent Whannou, Deng, Qili, Do, Jeonghyeok, Dong, Yu, Dutta, Saikat, Estrada, Dennis, Guo, Tiantong, Hsu, Po-Min, Huang, Ziling, Kim, Munchurl, Kong, Xiangzhen, Lee, David, Li, Xuelu, Liao, Tzu-Yi, Lin, Chang-Hong, Lin, Tsung-Nan, Liu, Jing, Ma, Lizhuang, Mandal, Murari, Mehra, Aryan, Metwaly, Kareem, Monga, Vishal, Narang, Pratik, Ouyang, Bing, Park, Jongmin, Qu, Yanyun, Raghunath, Navaneeth, Su, Tianqi, Sun, Bangyong, Sun, Chung-En, Timofte, Radu, Vasluianu, Florin-Alexandru, Wang, Meiqi, Wang, Zhan-Han, Wu, Haiyan, Wu, Pei-Yuan, Xie, Yuan, Yang, Tsung-Shan, Yu, Mingzhao, Yu, Zhe, Zhao, Xuan, Zhou, Hongyu   +51 more
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A Bayesian Framework for Single Image Dehazing considering Noise

The Scientific World Journal, 2014
The single image dehazing algorithms in existence can only satisfy the demand for dehazing efficiency, not for denoising. In order to solve the problem, a Bayesian framework for single image dehazing considering noise is proposed.
Dong Nan, Du-yan Bi, Chang Liu, Shi-ping Ma, Lin-yuan He   +4 more
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