Results 1 to 10 of about 5,293 (102)

Image dehazing algorithm based on deep transfer learning and local mean adaptation [PDF]

Scientific Reports
In recent years, haze has significantly hindered the quality and efficiency of daily tasks, reducing the visual perception range. Various approaches have emerged to address image dehazing, including image enhancement, restoration, and deep learning-based
Dongyang Shi, Sheng Huang
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DUNet: a novel dehazing model based on outdoor images [PDF]

Frontiers in Plant Science
Image dehazing technology is widely utilized in outdoor environments, especially in precision agriculture, where it enhances image quality and monitoring accuracy.
Wei Zhao, Wei Zhao, Qiusheng Zhang, Mingliang Li, Guanshi Ye, Zichen Liu, Mingyang Qi, Helong Yu, You Tang, You Tang, You Tang   +10 more
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AMSA-Net: attention-based multi-scale feature aggregation network for single image dehazing [PDF]

Frontiers in Neurorobotics
ProblemDeep learning technology promotes the development of single-image dehazing. However, many existing methods fail to fully consider the haze density and its spatial distribution, which limits the improvement of dehazing performance.Proposed ...
Shanqin Wang, Mengjun Miao, Mengjun Miao, Miao Zhang   +3 more
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Image dehazing algorithm based on light-value weighted allocation and multi-layer restricted perception [PDF]

Scientific Reports
In image dehazing, the dehazing performance in bright regions and the model’s robustness to noise are critical evaluation criteria. However, existing dehazing models often suffer from distortions in the bright areas and exhibit weak noise resistance.
Dongyang Shi, Sheng Huang, Wei Zhao
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Hazediff: A training-free diffusion-based image dehazing method with pixel-level feature injection. [PDF]

PLoS ONE
In the current environmental context, significant emissions generated by industrial and transportation activities, coupled with an unreasonable energy structure, have resulted in recurrent haze phenomena.
Xiaoxia Lin, Zhengao Li, Dawei Huang, Wancheng Feng, XinJun An, Lin Sun, Niuzhen Yu, Yan Li, Chunwei Leng   +8 more
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Adaptive haze pixel intensity perception transformer structure for image dehazing networks [PDF]

Scientific Reports
In the realm of deep learning-based networks for dehazing using paired clean-hazy image datasets to address complex real-world haze scenarios in daytime environments and cross-dataset challenges remains a significant concern due to algorithmic ...
Jing Wu, Zhewei Liu, Feng Huang, Rong Luo   +3 more
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SAD-Net: a full spectral self-attention detail enhancement network for single image dehazing [PDF]

Scientific Reports
Single-image dehazing technology plays a significant role in video surveillance and intelligent transportation. However, existing dehazing methods using vanilla convolution only extract features in the temporal domain and lack the ability to capture ...
Qingjun Niu, Kun Wu, Jialu Zhang, Zhenqi Han, Lizhuang Liu   +4 more
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An Efficient Dehazing Algorithm Based on the Fusion of Transformer and Convolutional Neural Network

Sensors, 2022
The purpose of image dehazing is to remove the interference from weather factors in degraded images and enhance the clarity and color saturation of images to maximize the restoration of useful features.
Jun Xu, Zi-Xuan Chen, Hao Luo, Zhe-Ming Lu   +3 more
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Enhance Low Visibility Image Using Haze-Removal Framework

IEEE Access, 2023
We proposed a novel image enhancement framework to raise the visibility of the image’s content. Our primary concern is eliminating haze-like effects and simultaneously increasing images’ brightness.
Ping Juei Liu
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Real-time Image Dehazing Realization Based on HLS [PDF]

Jisuanji gongcheng, 2016
Outdoor image or video often suffers from blurring and color deviation due to the atmospheric haze.This has a bad impact on the stability of outdoor video system.Because of high computational complexity of existing dehazing algorithms,it is difficult to ...
QI Le,ZHANG Xiaogang,YAO Hang
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