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

Nien Shiang Chou, Yu Chang Tzeng, Kun Shan Chen, Chih Tien Wang, Kuo Chin Fan

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

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.

Original languageEnglish
Article number033512
JournalJournal of Applied Remote Sensing
Volume3
Issue number1
DOIs
StatePublished - 2009

Keywords

  • detection
  • image processing
  • radar
  • remote sensing

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