摘要
针对高分辨率遥感影像中地物的复杂性和多变性带来的地物提取难点,提出了一种基于多层次规则的面向对象的典型地物提取方法。改进了基于区域增长的影像分割方法,利用小区域内的全局最优策略进行初始增长,避开了种子点的选择。利用影像分割得到的影像对象作为地物提取的基元,针对影像上典型地物选择提取特征,利用多层次的提取规则进行地物提取,总的提取精度达到87.1%。
An object-oriented typical ground objects extraction method based on multi-level rules is presented to solve the problem of ground objects extraction, which are complex and various in high resolution remote sensing image. Image segmentation method based on region is improved with an initial growing by global optimal principle, avoiding seed selecting. Im- age objects from image segmentation are used as primitive for extraction of ground objects extraction. The typical extraction features are analyzed for different ground objects. Multi- level rules are made based on different features and used to extract ground objects. And overall exaction accuracy of 87.1 % is achieved in the experiment.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2012年第6期636-639,共4页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金资助项目(40871172)
关键词
高分辨率遥感影像
影像分割
面向对象影像分析
地物提取
多层次规则
high-resolution remote sensing image
image segmentation
object-oriented im- age analysis
ground objects extraction l multi-level rules
