Real-time Defogging of Single Image of IoTs-based Surveillance Video Based on MAP
Due to the atmospheric scattering phenomenon in fog weather, the current monitoring video image defogging method cannot estimate the fog density of the image. This paper proposes a real-time defogging algorithm for single images of IoTs surveillance video based on maximum a posteriori (MAP). Under t...
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| Format: | Article |
| Language: | English |
| Published: |
Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2020-01-01
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| Series: | Tehnički Vjesnik |
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| Online Access: | https://hrcak.srce.hr/file/352002 |
| _version_ | 1797207171284336640 |
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| author | Xin Liu |
| author_facet | Xin Liu |
| author_sort | Xin Liu |
| collection | DOAJ |
| description | Due to the atmospheric scattering phenomenon in fog weather, the current monitoring video image defogging method cannot estimate the fog density of the image. This paper proposes a real-time defogging algorithm for single images of IoTs surveillance video based on maximum a posteriori (MAP). Under the condition of single image sequence, the posterior probability of the high-resolution single image is set to the maximum, which improves the MAP design super-resolution image reconstruction. This paper introduces fuzzy classification to calculate atmospheric light intensity, and obtains a single image of IoTs surveillance video by the atmospheric dissipation function. The improved algorithm has the largest signal-to-noise ratio after defogging, and the maximum value is as high as 40.99 dB. The average time for defogging of 7 experimental surveillance video images is only 2.22 s, and the real-time performance is better. It can be concluded that the proposed algorithm has excellent defogging performance and strong applicability. |
| first_indexed | 2024-04-24T09:18:40Z |
| format | Article |
| id | doaj.art-33dc030128c043ceb6a532f1d689d68f |
| institution | Directory Open Access Journal |
| issn | 1330-3651 1848-6339 |
| language | English |
| last_indexed | 2024-04-24T09:18:40Z |
| publishDate | 2020-01-01 |
| publisher | Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek |
| record_format | Article |
| series | Tehnički Vjesnik |
| spelling | doaj.art-33dc030128c043ceb6a532f1d689d68f2024-04-15T16:23:13ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in OsijekTehnički Vjesnik1330-36511848-63392020-01-012741262126910.17559/TV-20200527085338Real-time Defogging of Single Image of IoTs-based Surveillance Video Based on MAPXin Liu0Information Center, Southwest University, No. 2 Tiansheng Road, Beibei District, Chongqing, 400715, P. R. ChinaDue to the atmospheric scattering phenomenon in fog weather, the current monitoring video image defogging method cannot estimate the fog density of the image. This paper proposes a real-time defogging algorithm for single images of IoTs surveillance video based on maximum a posteriori (MAP). Under the condition of single image sequence, the posterior probability of the high-resolution single image is set to the maximum, which improves the MAP design super-resolution image reconstruction. This paper introduces fuzzy classification to calculate atmospheric light intensity, and obtains a single image of IoTs surveillance video by the atmospheric dissipation function. The improved algorithm has the largest signal-to-noise ratio after defogging, and the maximum value is as high as 40.99 dB. The average time for defogging of 7 experimental surveillance video images is only 2.22 s, and the real-time performance is better. It can be concluded that the proposed algorithm has excellent defogging performance and strong applicability.https://hrcak.srce.hr/file/352002Internet of Things (IoT)MAPmonitoringreal-time defoggingsingle imagevideo |
| spellingShingle | Xin Liu Real-time Defogging of Single Image of IoTs-based Surveillance Video Based on MAP Tehnički Vjesnik Internet of Things (IoT) MAP monitoring real-time defogging single image video |
| title | Real-time Defogging of Single Image of IoTs-based Surveillance Video Based on MAP |
| title_full | Real-time Defogging of Single Image of IoTs-based Surveillance Video Based on MAP |
| title_fullStr | Real-time Defogging of Single Image of IoTs-based Surveillance Video Based on MAP |
| title_full_unstemmed | Real-time Defogging of Single Image of IoTs-based Surveillance Video Based on MAP |
| title_short | Real-time Defogging of Single Image of IoTs-based Surveillance Video Based on MAP |
| title_sort | real time defogging of single image of iots based surveillance video based on map |
| topic | Internet of Things (IoT) MAP monitoring real-time defogging single image video |
| url | https://hrcak.srce.hr/file/352002 |
| work_keys_str_mv | AT xinliu realtimedefoggingofsingleimageofiotsbasedsurveillancevideobasedonmap |