| Title |
Study on the enhancement method of online monitoring image of dense fog environment with power lines in smart city |
| ID_Doc |
37508 |
| Authors |
Zhang, M; Song, ZT; Yang, JF; Gao, ML; Hu, YC; Yuan, C; Jiang, ZP; Cheng, W |
| Title |
Study on the enhancement method of online monitoring image of dense fog environment with power lines in smart city |
| Year |
2023 |
| Published |
|
| DOI |
10.3389/fnbot.2022.1104559 |
| Abstract |
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. |
| Author Keywords |
smart city; power lines; atmospheric scattering model; global atmospheric light; dark pixels |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000916848800001 |
| WoS Category |
Computer Science, Artificial Intelligence; Robotics; Neurosciences |
| Research Area |
Computer Science; Robotics; Neurosciences & Neurology |
| PDF |
https://www.frontiersin.org/articles/10.3389/fnbot.2022.1104559/pdf
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