| 基于eCognition的遥感图像面向对象分类方法研究 |
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| 引用本文： | 陈蕊,张继超.基于eCognition的遥感图像面向对象分类方法研究[J].测绘与空间地理信息,2020(2):91-95. |
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| 作者姓名： | 陈蕊 张继超 |
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| 作者单位： | 辽宁工程技术大学测绘与地理科学学院 |
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| 摘 要： | 随着高分辨率遥感图像越来越普及,传统的面向像元的图像分类方法不能满足对高分辨率遥感图像区域分类的需求,高分辨率遥感图像对图像处理的软件与硬件都有了更高的要求,因此,出现了相较于面向像元有着更高精度更为合理的面向对象分类方法,也更加适用于高分辨率遥感影像。本文通过采用面向对象分类的基本方法,运用eCognition软件,以山东省胶州市地区遥感影像为例,进行多尺度分割和面向对象分类。并用ENVI做监督分类,基于目视解译精度评定,对不同方法作出分析评价。结果表明:面向对象分类方法精度更高,更具有可靠性。
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| 关 键 词： | ECOGNITION 多尺度分割 遥感图像 面向对象 胶州地区分类 |
Study on Object-oriented Classification Method of Remote Sensing Image Based on eCognition |
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| CHEN Rui,ZHANG Jichao.Study on Object-oriented Classification Method of Remote Sensing Image Based on eCognition[J].Geomatics & Spatial Information Technology,2020(2):91-95. |
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| Authors: | CHEN Rui ZHANG Jichao |
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| Institution: | (School of Geomatics,Liaoning Technical University,Fuxin 123000,China) |
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| Abstract: | With the development of high resolution remote sensing image is more and more popular,the traditional pixel-based image classification method can no longer meet our classification of high resolution remote sensing image,and image processing software and hardware of high resolution remote sensing image are needed higher requirements. Therefore,there is a method called object-oriented classification which is not only has higher accuracy and more reasonable than pixel-oriented,but also more suitable for high resolution remote sensing images. In this paper,by using the basic method of object-oriented classification,using eCognition software,the remote sensing image of Jiaozhou in Shandong province is taken as an example to carry out multiresolution segmentation and object-oriented classification. And do the supervised classification with ENVI,Visual interpretation accuracy evaluation,make analysis and evaluation in different methods. The results show that the object-oriented classification method is more accurate and more reliable. |
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| Keywords: | eCognition multiresolution segmentation remote sensing images object-oriented Jiaozhou region classification |
| 本文献已被 CNKI 维普 等数据库收录！ |
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