Fractal Genetic Model in Change Detection of SAR images

被引：0
|
作者：
H. Aghababaee
J. Amini
Y. C. Tzeng
J. T. Sri Sumantyo
机构：
[1] University of Tehran,Department of Surveying and Geomatic Engineering
[2] National United University,Department of Electronic Engineering
[3] Chiba University,Microwave Remote Sensing Laboratory, Center for Environmental Remote Sensing
来源：
Journal of the Indian Society of Remote Sensing | 2013年 / 41卷
关键词：
Change Detection; Fractal Genetic Model; Fractal Geometry; Genetic Algorithm; SAR Images;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The paper presents an effective way of detecting the changes of multi-temporal synthetic aperture radar (SAR) images. An accurate unsupervised change detection method that combines the intensity information and the fractal dimension of SAR images is proposed based on the fractal genetic model (FGM). The model computes firstly the local fractal dimension of the SAR images to obtain the fractal image and next a new proposed measure (D) is calculated from the normalized ratio of SAR images and the normalized difference of fractal images. Finally, the change map is derived by minimizing a cost function using a genetic algorithm (GA) on the derived image from the measure. Experimental results of detecting changes from SAR images acquired by ASAR on board ENVISAT and ALOS-PALSAR reveal that the proposed method is an effective and efficient tool for change detection from SAR images.
引用
收藏
页码：739 / 747
页数：8
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