|
|||||
|
|
Fractal Genetic Model in Change Detection of SAR images |
|
| Authors: | H Aghababaee J Amini Y C Tzeng J T Sri Sumantyo |
| Institution: | 1. Department of Surveying and Geomatic Engineering, University of Tehran, Tehran, Iran 2. Department of Electronic Engineering, National United University, Miaoli, Taiwan 3. Microwave Remote Sensing Laboratory, Center for Environmental Remote Sensing, Chiba University, Chiba, Japan |
| Abstract: | 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. |
| Keywords: | |
| 本文献已被 SpringerLink 等数据库收录！ | |