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Journal of Applied Remote Sensing

On the application of a spatial chaotic model for detecting landcover changes in synthetic aperture radar images
Author(s): Nien-Shiang Chou; Yu-Chang Tzeng; Kun-Shan Chen; Chih-Tien Wang; Kuo-Chin Fan
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Paper Abstract

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.

Paper Details

Date Published: 1 February 2009
PDF: 16 pages
J. Appl. Remote Sens. 3(1) 033512 doi: 10.1117/1.3098431
Published in: Journal of Applied Remote Sensing Volume 3, Issue 1
Show Author Affiliations
Nien-Shiang Chou, National United Univ. (Taiwan)
Yu-Chang Tzeng, National United Univ. (Taiwan)
Kun-Shan Chen, National Central Univ. (Taiwan)
Chih-Tien Wang, National Central Univ. (Taiwan)
Kuo-Chin Fan, National Central Univ. (Taiwan)

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