Results 21 to 30 of about 820 (130)
Advances in Single-Image Dehazing via Unsupervised Learning [PDF]
Jisuanji kexue yu tansuoImage dehazing is an important research direction in image restoration for computer vision. Publicly available datasets are mainly dominated by large-scale synthetic hazy image datasets, while real-world hazy image datasets remain relatively limited.
ZHANG Mengmeng, YANG Ying, ZHAO Jia, WANG Huiling
doaj +1 more source
A Nighttime and Daytime Single-Image Dehazing Method
Applied Sciences, 2022 In this study, the requirements for image dehazing methods have been put forward, such as a wider range of scenarios in which the methods can be used, faster processing speeds and higher image quality.
Yunqing Tang, Yin Xiang, Guangfeng Chen
doaj +1 more source
Underwater Single Image Dehazing Using the Color Space Dimensionality Reduction Prior
IEEE Access, 2020 Underwater images suffer from low visibility and contrast caused by absorption and scattering, which leads to haze and some further limitations. The existing underwater single image dehazing methods cannot achieve a balance between the performance and ...
Yongbin Liu +4 more
doaj +1 more source
Single Image Dehazing Using Deep Learning
JOIV: International Journal on Informatics Visualization, 2021 Many real-world situations such as bad weather may result in hazy environments. Images captured in these hazy conditions will have low image quality due to microparticles in the air.
Cahyo Adhi Hartanto, Laksmita Rahadianti
doaj +1 more source
Deeplearning method for single image dehazing based on HSI colour space
Journal of Measurement Science and Instrumentation, 2021 The traditional single image dehazing algorithm is susceptible to the prior knowledge of hazy image and colour distortion.A new method of deep learning multi-scale convolution neural network based on HSI colour space for single image dehazing is proposed
CHEN Yong, TAO Meifeng, GUO Hongguang
doaj
Single Image Dehazing via NIN-DehazeNet
IEEE Access, 2019 Single image dehazing has always been a challenging problem in the field of computer vision. Traditional image defogging methods use manual features.
Kangle Yuan +3 more
doaj +1 more source
SINGLE IMAGE DEHAZING FOR VISIBILITY IMPROVEMENT [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015 Images captured in foggy weather conditions often suffer from poor visibility, which will create a lot of impacts on the outdoor computer vision systems, such as video surveillance, intelligent transportation assistance system, remote sensing space ...
Y. Zhai, D. Ji
doaj +1 more source
Autonomous Single-Image Dehazing: Enhancing Local Texture with Haze Density-Aware Image Blending
Remote SensingSingle-image dehazing is an ill-posed problem that has attracted a myriad of research efforts. However, virtually all methods proposed thus far assume that input images are already affected by haze. Little effort has been spent on autonomous single-image
Siyeon Han +3 more
doaj +1 more source
Image dehazing using two‐dimensional canonical correlation analysis
IET Computer Vision, 2015 Image dehazing is an important issue that interests both image processing and computer vision. In this study, image dehazing is modelled as an example‐based learning problem, and a novel dehazing algorithm using two‐dimensional (2D) canonical correlation
Liqian Wang, Liang Xiao, Zhihui Wei
doaj +1 more source
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 +5 more
doaj +1 more source