Korean Journal of Remote Sensing (대한원격탐사학회지)

Korean Society of Remote Sensing (대한원격탐사학회)
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New Unsupervised Classification Technique for Polarimetric SAR Images

  • Oh, Yi-Sok (Department of Electronic Information and Communication Engineering, Hongik University) ;
  • Lee, Kyung-Yup (Department of Electronic Information and Communication Engineering, Hongik University) ;
  • Jang, Ge-Ba (Department of Electronic Information and Communication Engineering, Hongik University)
  • Published : 2009.06.28
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Abstract

A new polarimetric SAR image classification technique based on the degree of polarization (DoP) and the co-polarized phase-difference (CPD) is presented in this paper. Since the DoP and the CPD of a scattered wave provide information on the randomness of the scattering and the type of scattering mechanisms, at first, the statistics of the DoP and CPD are examined with measured polarimetric SAR image data. Then, a DoP-CPD diagram with appropriate boundaries between six different classes is developed based on the SAR image. The classification technique is verified using the JPL AirSAR and ALOS PALSAR polarimetric data. The technique may have capability to classify an SAR image into six major classes; a bare surface, a village, a crown-layer short vegetation canopy, a trunk-layer short vegetation canopy, a crown-layer forest, and a trunk-dominated forest.

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References

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