OBJECT-ORIENTED CHANGE DETECTION BASED ON MULTI-SCALE APPROACH

被引：1

作者：

Jia, Yonghong ^{[1
]}

Zhou, Mingting ^{[1
]}

Ye Jinshan ^{[2
]}

机构：

[1] Wuhan Univ, Inst Remote Sensing & Informat Engn, Wuhan 430079, Hubei, Peoples R China

[2] Inst Remote Sensing & Digital Earth, Beijing 100101, Peoples R China

来源：

XXIII ISPRS CONGRESS, COMMISSION VII | 2016年 / 41卷 / B7期

关键词：

Optimal scale; multi-scale; CART tree; object-oriented techniques;

D O I：

10.5194/isprsarchives-XLI-B7-517-2016

中图分类号：

P9 [自然地理学];

学科分类号：

0705 ; 070501 ;

摘要：

The change detection of remote sensing images means analysing the change information quantitatively and recognizing the change types of the surface coverage data in different time phases. With the appearance of high resolution remote sensing image, object oriented change detection method arises at this historic moment. In this paper, we research multi-scale approach for high resolution images, which includes multi-scale segmentation, multi-scale feature selection and multi-scale classification. Experimental results show that this method has a stronger advantage than the traditional single-scale method of high resolution remote sensing image change detection.

引用

页码：517 / 522

页数：6

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