摘要
单木树冠提取对果树健康状态、营养成分、产量预测具有重要意义。无人机获取的高分辨率遥感影像作为低成本、低风险的数据源,为准确估计棵数、描绘树木冠层轮廓提供了新的技术手段。以往关于单木冠层轮廓提取的研究大多集中在森林或稀疏果园,以局部最大值滤波结果作为基于标记分水岭算法的种子点,该方法在密植型果园的表现并不理想。提出了一种适用于密植型果园、以区域型种子块作为标记的分水岭算法,通过最大似然法提取果树冠层生成冠层数字表面模型,利用高斯滤波结合形态学开运算及自适应阈值分割方法生成区域型种子块,并执行基于种子块标记的分水岭算法,实现密植型果园单木分割。实例研究结果表明,总体棵数查全率为95.22%,查准率为99.09%,得到单木轮廓提取总体准确率为93.45%,总体欠分割误差为5.87%,总体过分割误差为0.90%。与局部最大值种子点提取结果对比,总体准确度提高18.66%,精细树冠轮廓提取精度提高17.75%,可为地形平缓地区密植型果园单棵果树树冠提取提供参考。
Objectives:Single tree canopy extraction is of great significance for fruit tree health status,nutritional composition,and yield prediction.As a low-cost,low-risk data source,high-resolution remote sensing images obtained by drones provide new technical means for accurately estimating tree numbers and delineating tree canopy profiles.Using unmaned aerial vehicle(UAV)digital images as the data source,a single-tree segmentation algorithm based on regional seed blocks is proposed to solve the single-tree segmentation problem of densely planted fruit trees.Methods:The canopy of the fruit tree is extracted by the maximum likelihood method to generate digital surface model(DSM)of the canopy,and Gaussian filter is combined with morphological opening and self-adapted threshold segmentation generates regional seed blocks as the basis for tree statistics and as the marker of the marked-controlled watered segmentation.Results:The results show that the overall tree recall rate is 95.22%,the precision rate is 99.09%.The overall accuracy rate of single tree contour extraction is 93.45%,the overall omission error is 5.87%,and the overall commission error is 0.90%.Compared with the previous local maximum seed point extraction results,the overall accuracy is 18.66%higher,and the precision of the fine crown contour extraction is 17.75%higher.Conclusions:The watershed method based on the regional seed block can effectively prevent the overlapping area of the canopy from being repeatedly divided into multiple fruit trees.On the basis of preserving the canopy outline of the fruit tree to the greatest extent,the segmentation error of the fruit tree is reduced.It provides a reference for the method of extracting the crown of a single fruit tree in a densely planted orchard in flat terrain.
作者
徐伟萌
杨浩
李振洪
程金鹏
林哈特
杨贵军
XU Weimeng;YANG Hao;LI Zhenhong;CHENG Jinpeng;LIN Hate;YANG Guijun(College of Geological Engineering and Geomatics,Chang'an University,Xi'an 710054,China;Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture and Rural Affairs,Beijing 100097,China;Information Technology Research Center,Beijing Academy of Agriculture and Forestry Sciences,Beijing 100097,China;School of Information Science and Technology,Beijing Forestry University,Beijing 100083,China)
出处
《武汉大学学报(信息科学版)》
EI
CAS
CSCD
北大核心
2022年第11期1906-1916,共11页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金(42171303)
国家重点研发计划(2017YFE0122500)
广东省重点领域研发计划(2019B020216001)。
关键词
无人机
单木分割
标记分水岭算法
数码影像
unmaned aerial vehicle(UAV)
tree crown delineation
marked-controlled watered segmentation
digital image