On the application of a spatial chaotic model for detecting landcover changes in synthetic aperture radar images

We present a change detection method for terrain covers from multi-temporal SAR images based on a spatial chaotic model which is known to adequately characterize the coherent process of SAR imaging. The major problem of SAR change detection rises from both the presence of speckle noise and the pixel...

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Bibliographic Details
Published in:Journal of Applied Remote Sensing 2009-02, Vol.3 (1), p.033512-0335116
Main Authors: Chou, Nien-Shiang, Tzeng, Yu-Chang, Chen, Kun Shan, Wang, Chih-Tien, Fan, Kuo-Chin
Format: Article
Language:English
Subjects:
Algorithms
Change detection
Chaos theory
detection
Error detection
image processing
Noise
radar
Remote sensing
Synthetic aperture radar
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Summary:We present a change detection method for terrain covers from multi-temporal SAR images based on a spatial chaotic model which is known to adequately characterize the coherent process of SAR imaging. The major problem of SAR change detection rises from both the presence of speckle noise and the pixel mis-registration that are commonly seen in the remote sensing image. By means of chaotic model, we first transform the images to fractal domain and then perform the CFAR detection. Simulated tests are conducted to quantitatively evaluate the impacts of these two major error sources on detection rate. Results from satellite SAR for landcover change detection clearly show that the proposed algorithm not only the speckle noise can be effectively suppressed without scarifying the spatial resolution; the excruciating mis-registration error was taken into account and removed.
ISSN:1931-3195
1931-3195
DOI:10.1117/1.3098431