Study on the enhancement method of online monitoring image of dense fog environment with power lines in smart city
In this research, an image defogging algorithm is proposed for the electricity transmission line monitoring system in the smart city. The electricity transmission line image is typically situated in the top part of the image which is rather thin in size. Because the electricity transmission line is...
Main Authors: | , , , , , , , |
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Format: | Article |
Language: | English |
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Frontiers Media S.A.
2023-01-01
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Series: | Frontiers in Neurorobotics |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fnbot.2022.1104559/full |
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author | Meng Zhang Zhitao Song Jianfei Yang Mingliang Gao Yuanchao Hu Chi Yuan Zhipeng Jiang Wei Cheng |
author_facet | Meng Zhang Zhitao Song Jianfei Yang Mingliang Gao Yuanchao Hu Chi Yuan Zhipeng Jiang Wei Cheng |
author_sort | Meng Zhang |
collection | DOAJ |
description | In this research, an image defogging algorithm is proposed for the electricity transmission line monitoring system in the smart city. The electricity transmission line image is typically situated in the top part of the image which is rather thin in size. Because the electricity transmission line is situated outside, there is frequently a sizable amount of sky in the backdrop. Firstly, an optimized quadtree segmentation method for calculating global atmospheric light is proposed, which gives higher weight to the upper part of the image with the sky region. This prevents interference from bright objects on the ground and guarantees that the global atmospheric light is computed in the top section of the image with the sky region. Secondly, a method of transmission calculation based on dark pixels is introduced. Finally, a detail sharpening post-processing based on visibility level and air light level is introduced to enhance the detail level of electricity transmission lines in the defogging image. Experimental results indicate that the algorithm performs well in enhancing the image details, preventing image distortion and avoiding image oversaturation. |
first_indexed | 2024-04-11T00:35:08Z |
format | Article |
id | doaj.art-a2d8f5a15df24b699d295b098eaddbde |
institution | Directory Open Access Journal |
issn | 1662-5218 |
language | English |
last_indexed | 2024-04-11T00:35:08Z |
publishDate | 2023-01-01 |
publisher | Frontiers Media S.A. |
record_format | Article |
series | Frontiers in Neurorobotics |
spelling | doaj.art-a2d8f5a15df24b699d295b098eaddbde2023-01-06T22:40:07ZengFrontiers Media S.A.Frontiers in Neurorobotics1662-52182023-01-011610.3389/fnbot.2022.11045591104559Study on the enhancement method of online monitoring image of dense fog environment with power lines in smart cityMeng Zhang0Zhitao Song1Jianfei Yang2Mingliang Gao3Yuanchao Hu4Chi Yuan5Zhipeng Jiang6Wei Cheng7State Grid Hubei Power Supply Limited Company Ezhou Power Supply Company, Ezhou, ChinaState Grid Hubei Power Supply Limited Company Ezhou Power Supply Company, Ezhou, ChinaSchool of Electrical and Electronic Engineering, Shandong University of Technology, Zibo, ChinaSchool of Electrical and Electronic Engineering, Shandong University of Technology, Zibo, ChinaSchool of Electrical and Electronic Engineering, Shandong University of Technology, Zibo, ChinaState Grid Hubei Power Supply Limited Company Ezhou Power Supply Company, Ezhou, ChinaState Grid Hubei Power Supply Limited Company Ezhou Power Supply Company, Ezhou, ChinaState Grid Hubei Power Supply Limited Company Ezhou Power Supply Company, Ezhou, ChinaIn this research, an image defogging algorithm is proposed for the electricity transmission line monitoring system in the smart city. The electricity transmission line image is typically situated in the top part of the image which is rather thin in size. Because the electricity transmission line is situated outside, there is frequently a sizable amount of sky in the backdrop. Firstly, an optimized quadtree segmentation method for calculating global atmospheric light is proposed, which gives higher weight to the upper part of the image with the sky region. This prevents interference from bright objects on the ground and guarantees that the global atmospheric light is computed in the top section of the image with the sky region. Secondly, a method of transmission calculation based on dark pixels is introduced. Finally, a detail sharpening post-processing based on visibility level and air light level is introduced to enhance the detail level of electricity transmission lines in the defogging image. Experimental results indicate that the algorithm performs well in enhancing the image details, preventing image distortion and avoiding image oversaturation.https://www.frontiersin.org/articles/10.3389/fnbot.2022.1104559/fullsmart citypower linesatmospheric scattering modelglobal atmospheric lightdark pixels |
spellingShingle | Meng Zhang Zhitao Song Jianfei Yang Mingliang Gao Yuanchao Hu Chi Yuan Zhipeng Jiang Wei Cheng Study on the enhancement method of online monitoring image of dense fog environment with power lines in smart city Frontiers in Neurorobotics smart city power lines atmospheric scattering model global atmospheric light dark pixels |
title | Study on the enhancement method of online monitoring image of dense fog environment with power lines in smart city |
title_full | Study on the enhancement method of online monitoring image of dense fog environment with power lines in smart city |
title_fullStr | Study on the enhancement method of online monitoring image of dense fog environment with power lines in smart city |
title_full_unstemmed | Study on the enhancement method of online monitoring image of dense fog environment with power lines in smart city |
title_short | Study on the enhancement method of online monitoring image of dense fog environment with power lines in smart city |
title_sort | study on the enhancement method of online monitoring image of dense fog environment with power lines in smart city |
topic | smart city power lines atmospheric scattering model global atmospheric light dark pixels |
url | https://www.frontiersin.org/articles/10.3389/fnbot.2022.1104559/full |
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