基于Agisoft Metashape图像拼接的无人机环境热像监测应用研究

徐旭; 康青; 陈善静; 王正刚; 茅雷

基于Agisoft Metashape图像拼接的无人机环境热像监测应用研究

徐旭^{1, 2,},
康青¹,
陈善静¹,
王正刚¹,
茅雷¹

1.
陆军勤务学院, 重庆 401311
2.
中国人民解放军93055部队, 沈阳 110020

基金项目:

重庆市自然科学基金项目 CSTC2020JCYJ-KSXMX0156

重庆市教发科学技术研究项目 KJQN201912905

详细信息

作者简介:
徐旭（1993-），男，辽宁沈阳人，助理工程师，硕士研究生，研究方向为军事建筑安全与技术。E-mail: 526668372@qq.com

中图分类号: TN219
计量
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- PDF下载量: 41
- 被引次数: 0
出版历程
- 收稿日期: 2021-12-30
- 修回日期: 2022-04-11
- 刊出日期: 2023-01-20

Application of UAV Environmental Thermography Monitoring Based on Agisoft Metashape Image Mosaic

1.
Army Logistics University, Chongqing 401311, China
2.
93055 Unit, PLA, Shenyang 110020, China

摘要

摘要: 为实现大面积区域的环境热像监测，本文以重庆某高校训练场为例，研究了一种无人机区域环境热像监测技术。通过无人机采集环境热像，使用Agisoft Metashape软件进行无人机热红外影像拼接处理，并利用处理后的热红外影像进行环境热像监测与目标分析。研究表明，利用该技术可实现区域热红外影像的快速处理，并且处理成果可以为环境热像监测与目标热像分析提供有效参考与基础资料。
- Agisoft Metashape /
- 影像拼接 /
- 环境监测 /
- 热像分析
Abstract: To realize environmental thermal image monitoring in a large area, this study took a university training field in Chongqing as an example to investigate UAV regional environmental thermal image monitoring technology. First, the UAV was used for environmental thermal image acquisition, and the Agisoft Metashape software was used for UAV thermal infrared mosaic thermal image processing. The processed thermal infrared images were used for environmental thermal image monitoring and target analysis. Experiments showed that the technology can realize fast processing of regional thermal infrared images, and the processing results can provide an effective reference and basic data for environmental thermal image monitoring and target thermal image analysis.
- Agisoft Metashape /
- image stitching /
- environmental monitoring /
- thermal image analysis

HTML全文

图 1 搭载XT2热成像镜头的M600无人机

Figure 1. XT2 thermal imaging lens carried by M600

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图 2 照片导入后效果

Figure 2. The effect after Photo Import

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图 3 对齐照片后生成的疏点云

Figure 3. Sparse point cloud generated after aligning photos

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图 4 生成网格后的模型

Figure 4. Model after generating grids

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图 5 区域热红外影像处理后效果

Figure 5. The effect of regional thermal infrared image processing

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图 6 某试验区域可见光影像

Figure 6. Visible waveband image of a test area

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图 7 疏点云生成失败

Figure 7. Failure to generate a sparse cloud

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图 8 两种源数据的处理结果无明显差异

Figure 8. There is no obvious difference between the processing results of two source data

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图 9 需要重点关注与监测的显著热目标

Figure 9. Indigenous hot targets required focus and monitoring

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图 10 污染物堆积处的可见光影像

Figure 10. The imagines of pollutant accumulation

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图 11 测温区不同对象设置测温点

Figure 11. Setting temperature measuring points for objects

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表 1 禅思XT2技术参数

Table 1. Technical parameters of XT2

	Thermal imaging camera	vision camera
Resolution	640×512	4K: 3840×2160
Resolution	640×512	FHD: 1920×1080
Focal Length (mm)	19	8
Active Picture Elements	—	12 million
Wavelength coverage(μm)	7.5-13.5	—
Sensitivity (mk@f/1.0)	< 50	—

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表 2 测温区内各测温点温度信息

Table 2. Temperature information of temperature measuring points

Numbering	Object category	Temperature sensing point	Temperature point display temperature/℃
1	Gravel soil road	SP1	9.3
		SP2	9.8
		SP3	9.5
2	Bagged domestic waste	SP4	10.2
		SP5	11.5
		SP6	12.2
3	Plant	SP7	8.5
		SP8	8.8
		SP9	8.9
4	White wastes	SP10	8.2
		SP11	8.0
		SP12	8.0
5	Waste roofs	SP13	8.1
6	Engineering dustproof net	SP14	8.7
6	Engineering dustproof net	SP15	8.3
7	Climax temperature	Red temperature point	15.3
8	Lowest temperature point	Blue temperature point	5.8

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