南京大学学报（自然科学版）Issue(5)：1049-1057,9.DOI:10.13232/j.cnki.jnju.2015.05.016
面向对象变化检测中多时相图像分割模式影响评价
Evaluating the effectiveness of multi-temporal image segmentation on object-based change detection
摘要
Abstract
Object-based image analysis (OBIA)has shown improved performances over the classical pixel-based methods,and object-based change detection(OBCD)is an important part of OBIA.From the perspective for object extraction of multi-temporal image data,the image segmentation can be categorized into three different models:two time data stacking as a whole for segmentation,which produce spatially corresponding objects;Extracting objects from one time data and assigning to the other time data without segmentation;segmenting independently for the two time data.The evaluation of three multi-temporal image segmentation models remains a critical significance because objects in different models are of various sizes and shapes.In this paper we use change vector analysis to divide objects into changed and unchanged objects,the changed objects acquired from the three image segmentation models are analyzed using qualitative and quantitative comparison,and the standard evaluation map is acquired by the artificial visual interpretation.From the comparison of three multi-temporal image segmentation models,it shows that the first image segmentation model has the highest overall accuracy and Kappa coefficient on both of the two study areas.In practical OBCD applications,we can choose the appropriate image segmentation models according to the status of study area and application purposes.关键词
高分辨率遥感图像/面向对象变化检测/多时相图像分割/变化检测精度评价Key words
high resolution remote sensing image/object-based change detection/multi-temporal image segmentation/change detection accuracy assessment分类
信息技术与安全科学引用本文复制引用
胡永月,肖鹏峰,冯学智,张学良,袁敏..面向对象变化检测中多时相图像分割模式影响评价[J].南京大学学报（自然科学版）,2015,(5):1049-1057,9.基金项目
浙江省科技计划(2014F50022),江苏高校“青蓝工程”(201423) （2014F50022）
