基于形态学纹理特征的高分辨率遥感影像变化检测  

High-Resolution Remote Sensing Image Change Detection Based on Morphological Texture Features

作　　者：丁海勇[1] 罗麒杰 王晓英[1] 

机构地区：[1]南京信息工程大学地理与遥感学院,江苏南京

出　　处：《测绘科学技术》2017年第3期143-151,共9页Geomatics Science and Technology

基　　金：国家自然科学基金项目“城市边缘区地表组分温度反演模型的构建”(编号:41571350);南京信息工程大学大学生创新创业项目,项目号:201510300067、201610300302。

摘　　要：由于高分辨率遥感影像数据可以提供更加精细和准确的地表类别信息,它已经成为土地利用覆盖变化研究的主要数据源之一。本文以15米空间分辨率的遥感影像为数据源,利用数学形态学运算得到了高分辨率遥感影像的纹理特征图像序列,进行了决策树分类,得到了土地利用变化前后期的图像类别信息,采用图像变化轨迹法来进行变化检测。实验结果证明了本文提出算法的有效性,为更加实用的变化检测研究打下了基础。Because high-resolution remote sensing image data can provide more detailed and accurate surface classification information, it has become one of the main data sources of land use change research. In this paper, the remote sensing image with spatial resolution of 15 m is used as the data source, and the texture feature sequence of high resolution remote sensing image is obtained by mathematical morphology. The decision tree classification is made, and the image classification information is obtained before and after land use change. Land use change analysis was carried out by comparative method. The experimental results show that the proposed algorithm is effective and provides the basis for more practical research on the change detection.

关 键 词：高分辨率遥感影像 数学形态学滤波 决策树 土地利用变化 

分 类 号：TP7[自动化与计算机技术—检测技术与自动化装置]