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复杂背景下航拍图像的电力线自动提取算法
引用本文:陈竹安,邹梓龙,徐志芳,彭嘉琪,施陈敬,洪志强.复杂背景下航拍图像的电力线自动提取算法[J].测绘通报,2022,0(4):37-43.
作者姓名:陈竹安  邹梓龙  徐志芳  彭嘉琪  施陈敬  洪志强
作者单位:1. 东华理工大学测绘工程学院, 江西 南昌 330013;2. 自然资源部环鄱阳湖区域矿山环境监测与治理重点试验室, 江西 南昌 330013;3. 广东国地资源与环境研究院, 广东 广州 510000;4. 南昌工学院, 江西 南昌 330108
基金项目:国家自然科学基金(51708098);
摘    要:无人机对电力线巡检的关键问题是如何从复杂背景的航拍图像中准确地提取电力线。本文提出了一种基于二维变分模态分解 (2D-VMD) 提取电力线的新算法。首先对原始航拍图像进行预处理,加快数据处理速度;然后采用2D-VMD算法对预处理后的图像进行分解,通过改进后的点锐度算法,选取带有电力线特征的IMF分量图,并利用Roberts算子进行边缘检测;最后利用形态学改进的Hough变换,完成对电力线的提取。试验结果表明,本文方法比传统的Canny算子结合Hough变换方法、LSD方法、Roberts 算法结合形态学改进的Hough变换方法更具精确性、抗噪性、自动化。

关 键 词:复杂背景  二维变分模态分解  Roberts算法  形态学  Hough变换  
收稿时间:2021-03-04
修稿时间:2021-12-28

Automatic power line extraction algorithm for aerial image under complex background
CHEN Zhu'an,ZOU Zilong,XU Zhifang,PENG Jiaqi,SHI Chenjing,HONG Zhiqiang.Automatic power line extraction algorithm for aerial image under complex background[J].Bulletin of Surveying and Mapping,2022,0(4):37-43.
Authors:CHEN Zhu'an  ZOU Zilong  XU Zhifang  PENG Jiaqi  SHI Chenjing  HONG Zhiqiang
Institution:1. Faculty of Geomatics, East China University of Technology, Nanchang 330013, China;2. Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake, Ministry of Natural Resources, Nanchang 330013, China;3. Guangdong Guodi Institute of Resource and Evironment, Guangzhou 510000, China;4. Nanchang Institute of Science and Technology, Nanchang 330108, China
Abstract:The key problem of UAV power line inspection is how to accurately extract power lines from aerial images with complex background. This paper proposes a new algorithm for power line extraction based on two-dimensional variational mode decomposition (2D-VMD). Firstly, the original aerial image is preprocessed to speed up data processing. Secondly, 2D-VMD algorithm is utilized to decompose the preprocessed image. The IMF component graph with power line features is selected by the improved point sharpness algorithm and edge detection is performed by Roberts operator. Finally, the power lines are extracted by morphological modification of Hough transform. Experimental results show that the proposed method is more accurate, noise resistant and automatic than the traditional Canny edge detection combined with Hough transform method, line segment detector (LSD) method, Roberts edge detection and morphological improved Hough transform method.
Keywords:complex background  two-dimensional variational mode decomposition (2D-VMD)  Roberts algorithm  morphology  Hough transform  
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