摘要
提出了一种基于时空关系的遥感影像变化检测及类型识别方法。该方法通过影像分割获取像斑,利用最大似然法(maximum likelihood method,ML)获取初始分类结果,通过地物的类别转移矩阵(class transition matrix,CTM)和类别邻接矩阵(class adjacency matrix,CAM)定量地描述各地物类别之间的时间关系和空间关系。实验结果显示,本方法优于分类后比较法。
A method for change detection and change type recognition of remote sensing images based on spatiotemporal relationship is proposed in this paper. Image segmentation is adopted to get image segments for original image classification using maximum likelihood method(ML). Quantitative spatiotemporal relationship is described by class transition matrix(CTM) and class adiacency matrix(CAM). In order to verify the validity of the algorithm, the method proposed in the paper is compared with the post classification comparison(PCC) method. Experimental results confirm that the proposed method can provide higher accuracy.
出处
《武汉大学学报(信息科学版)》
EI
CSCD
北大核心
2013年第5期533-537,共5页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金资助项目(41101412)
中央高校基本科研业务费专项基金资助项目(3101009
20102130201000139
CHD2011JC011)
关键词
时空关系
变化类型识别
变化检测
spatiotemporal relationship
change type recognition
change detection