摘要
激光测高仪通过发射激光束并接收其反射信号来测量目标的高度,在此过程中会面临大气湍流、背景光等干扰,导致光斑形状不规则或光强分布不均匀,影响光斑质心测量的准确性。针对干扰导致的测量误差问题,提出视觉传达技术下激光测高仪光斑质心提取方法。利用中值滤波去除初始光斑图像噪声,并应用最大熵阈值分割方法,分割图像前景和背景,确定光斑目标范围;由此,使用最小二乘椭圆拟合法拟合光斑质心边界点,计算图像中所有光斑和聚类中心之间的欧氏距离,运用累积矩阵法实现光斑质心提取。实验结果表明,所提方法对光斑质心提取的标准差在0.1以内,且AUC下曲线面积更接近1。说明所提方法能够准确确定光斑边界,保证质心位置提取的精度。
The laser altimeter measures the height of a target by emitting a laser beam and receiving its reflected signal.During this process,it may face interference from atmospheric turbulence,background light,resulting in irregular spot shape or uneven light intensity distribution,which affects the accuracy of spot centroid measurement.Aiming at the measurement error caused by interference,a method for extracting the centroid of laser altimeter spot under visual communication technology is proposed.Using median filtering to remove initial speckle image noise,and applying maximum entropy threshold segmentation method to segment the foreground and background of the image,determine the target range of the speckle.Therefore,the least squares ellipse fitting method is used to fit the centroid boundary points of the light spots,and the Euclidean distance between all light spots and cluster centers in the image is calculated.The cumulative matrix method is used to extract the centroid of the light spots.The experimental results show that the standard deviation of the proposed method for extracting the centroid of the light spot is within 0.1,and the curve area under AUC is closer to 1.The proposed method can accurately determine the boundary of the light spot and ensure the accuracy of extracting the centroid position.
作者
闫昌凤
彭鹏
罗梦贞
YAN Changfeng;PENG Peng;LUO Mengzhen(Guilin University,Guilin Guangxi 541004,China;Guilin Institute of Information Technology,Guilin Guangxi 541004,China;Institute of Technology,Guilin University,Guilin Guangxi 541004,China)
出处
《激光杂志》
北大核心
2025年第10期238-242,共5页
Laser Journal
基金
广西高校中青年教师科研基础能力提升项目(No.2024KY1736)。
关键词
视觉传达
激光测高仪
质心提取
中值滤波
最小二乘椭圆
欧氏距离
累计矩阵
visual communication
laser altimeter
centroid extraction
median filtering
least squares ellipse
euclidean distance
cumulative matrix
