Unmanned Aerial Vehicle Image Dehazing Algorithm Based on Simple Linear Iterative Clustering Optimization and Its Application in Wind Farm
In order to solve the problem that the unmanned aerial vehicle (UAV) image is not clear due to the influence of fog particles, a UAV image dehazing algorithm based on simple linear iterative clustering (SLIC) optimization was proposed. Through the physical model of fog imaging, the prior law of dark...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Editorial Department of Power Generation Technology
2020-12-01
|
| Series: | 发电技术 |
| Subjects: | |
| Online Access: | https://www.pgtjournal.com/EN/10.12096/j.2096-4528.pgt.20006 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | In order to solve the problem that the unmanned aerial vehicle (UAV) image is not clear due to the influence of fog particles, a UAV image dehazing algorithm based on simple linear iterative clustering (SLIC) optimization was proposed. Through the physical model of fog imaging, the prior law of dark channel, homogeneous filtering and SLIC algorithm, the influence of white area and uneven light in power inspection image was improved, the efficiency of UAV image dehazing was improved, and the adaptive calculation of atmospheric light intensity parameters was carried out to prevent the distortion in the dehazing process. The experimental results show that the algorithm can effectively restore the original details of the power inspection image. Through the comparison of subjective visual evaluation and fusion of a variety of objective evaluation indexes, it shows the superiority of the algorithm compared with the traditional algorithms. |
|---|---|
| ISSN: | 2096-4528 |