An improved method for edge detection based on neighbor distance for processing hemispheric photography  

一种基于邻居距离的半球照片边缘检测新方法

作　　者：Yasi Liu Dayong Fan Han Sun Xiangping Wang 

机构地区：[1]State Key Laboratory of Effcient Production of Forest Resources,School of Ecology and Nature Conservation,Beijing Forestry University,Beijing 100083,China [2]The Key Laboratory for Silviculture and Conservation of Ministry of Education,Beijing Forestry University,Beijing 100083,China

出　　处：《Journal of Plant Ecology》2024年第2期134-145,共12页植物生态学报（英文版）

基　　金：supported by the Fang Jingyun ecological study studio of Yunnan province,the National Natural Science Foundation of China(32271652,32201258);the Major Program for Basic Research Project of Yunnan Province(202101BC070002)。

摘　　要：Hemisphere photos are now widely applied to provide information about solar radiation dynamics,canopy structure and their contribution to biophysical processes,plant productivity and ecosystem properties.The present study aims to improve the original‘edge detection’method for binary classifcation between sky and canopy,which works not well for closed canopies.We supposed such inaccuracy probably is due to the infuence of sky pixels on their neighbor canopy pixels.Here,we introduced a new term‘neighbor distance’,defned as the distance between pixels participated in the calculation of contrast at the edges between classifed canopy and sky,into the‘edge detection’method.We showed that choosing a suitable neighbor distance for a photo with a specifc gap fraction can signifcantly improve the accuracy of the original‘edge detection’method.We developed an ND-IS(Neighbor Distance-Iteration Selection)method that can automatically determine the threshold values of hemisphere photos with high accuracy and reproductivity.It combines the modifed‘edge detection’method and an iterative selection method,with the aid of an empirical power function for the relationship between neighbor distance and manually verifed gap fraction.This procedure worked well throughout a broad range of gap fractions(0.019-0.945)with different canopy compositions and structures,in fve forest biomes along a broad gradient of latitude and longitude across Eastern China.Our results highlight the necessity of integrating neighbor distance into the original‘edge detection’algorithm.The advantages and limitations of the method,and the application of the method in the feld were also discussed.半球照片被广泛应用于植物生态研究领域,它提供了太阳辐射动态、冠层结构特征及两者对群落生物物理过程、生产力和生态系统特性的贡献等重要信息。本研究旨在改进用于天空和冠层二元分类的原始“边缘检测”方法,该方法对于郁闭的冠层分类效果不佳。究其原因,可能是由于郁闭的冠层下天空像素对其相邻冠层像素的影响较大所致。为此,我们在“边缘检测”方法中引入了一个新参数“邻居距离”,定义为参与分类冠层和天空之间边缘对比度计算的两类像素之间的距离。研究发现,对于具有特定间隙分数的半球照片,选择合适的邻居距离可以显著提高原始“边缘检测”方法的准确性。在建立了邻居距离与手动验证间隙分数之间关系的经验幂函数基础上,我们开发了一种ND-IS(邻居距离-迭代选择)新方法,该方法可以高精度自动确定半球照片二元分类的阈值。我们在中国东部沿纬度的五个森林生物群落(间隙分数在0.019至0.945之间)对该方法进行了验证,其二元分类精度相对于原始“边缘检测”方法无论在精度还是可重复性上均有显著提升。本研究结果强调了将邻居距离整合到原始“边缘检测”算法中的必要性。本文还讨论了该方法在野外环境中应用中的优点和局限性。

关 键 词：hemisphere photos ‘edge detection’method neighbor distance gap fraction forest 

分 类 号：Q94[生物学—植物学]