An adaptive and iterative method of urban area extraction from SAR images

被引：21

作者：

He, Chu ^{[1
]}

Xia, Gui-song ^{[1
]}

Sun, Hong ^{[1
]}

机构：

[1] Wuhan Univ, Elect Informat Sch, Dept Commun Engn, Signal Proc Lab, Wuhan 430079, Peoples R China

来源：

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2006年 / 3卷 / 04期

基金：

中国国家自然科学基金;

关键词：

adaptive and iterative (AI); ffmax algorithm; synthetic aperture radar (SAR) image; urban area extraction;

D O I：

10.1109/LGRS.2006.878447

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

This letter presents a new method for unsupervised urban area extraction from synthetic aperture radar (SAR) images based on the ffmax algorithm proposed by C. Gouinaud specially for acquiring urban areas in SPOT imagery. According to the statistical characteristics of urban areas, an adaptive and iterative method based on the low-level extraction given by the ffmax algorithm using a large window is proposed. Experimental results on real SAR images show that the proposed automatic method works quickly and can preserve the borders of urban areas as well as avoid the disturbance of other classes and the extractions of urban areas are reliable and precise.

引用

页码：504 / 507

页数：4

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