| 面向对象的高分辨率遥感影像分割精度评价方法 |
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| 引用本文： | 朱成杰,杨世植,崔生成,程伟,程晨.面向对象的高分辨率遥感影像分割精度评价方法[J].强激光与粒子束,2015,27(6):061007. |
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| 作者姓名： | 朱成杰 杨世植 崔生成 程伟 程晨 |
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| 作者单位： | 1.中国科学院 安徽光学精密机械研究所 光学遥感中心, 合肥 230031 ; |
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| 摘 要： | 在参考监督评价法原理的基础上,提出了三个高分辨率遥感影像分割精度评价指标:准确度、查全率和相对相似性,并以此为基础提出了遥感影像分割精度的评价方法。针对监督评价法的参考对象匹配问题,提出了一种双向局部最优对象匹配方法。同时,通过安徽省淮南市高分一号遥感影像分割结果的精度评价,进行了实验验证。结果表明:该评价指标能够较好地反映分割结果的优劣,符合地物对象分割的真实分布;还可为遥感影像分割算法的参数设置和多尺度分割的最优尺度选择提供依据。
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| 关 键 词： | 面向对象 影像分割 监督评价法 精度评价 对象匹配 |
| 收稿时间： | 2015-02-05 |
Accuracy evaluating method for object-based segmentation of high resolution remote sensing image |
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| Affiliation: | 1.Center of Optical Remote Sensing,Anhui Institute of Optics and Fine Mechanics,Chinese Academy of Sciences,Hefei 230031,China;2.Department of Automation,College of Electronic Engineering,Anhui University of Science and Technology,Huainan 232001,China;3.Key Laboratory of Optical Calibration and Characterization,Chinese Academy of Sciences,Hefei 230031,China |
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| Abstract: | Based on the principles of supervised evaluation method, the paper puts forward three evaluation indices of the high resolution remote sensing image segmentation: precision, recall and relative similarity, and brings forward the method of precision evaluation of remote sensing image segmentation. With respect to the reference object matching problem of the supervised evaluation method, the paper proposes the matching method of bidirectional local optimal object. Validation of the proposed evaluation indices is carried out using GF-1 high resolution remote sensing image in Huainan city, Anhui province, China. The results show that the proposed evaluation indices can reflect very well the quality of the segmentation results and are consistent with the real distribution of ground landcover segmentation, and also provide the basic reference to parameter setting for the image segmentation algorithm and optimal scale selection for the multi-scale segmentation. |
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