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  • ACRS 2000


    AirSAR/MASTER


    Analysis of Polarization Signatures and Textural Features for Airborne Pi-Sar Images

    5. Discussions
    The first, fluctuations of polarization signatures caused by including shadows in partial area are considered. Back-scattering for the shadow is much smaller, so that the elements of Mueller matrix are also smaller wholly. Hence, averaged values of the elements are smaller than the area excluding shadows relatively. Therefore, values of s0 become smaller, too. On the other hand, the shapes of polarization signature diagrams are preserved because back-scattering for shadows depend on the polarization scarcely.

    Next, the polarization properties of textural features are considered. For the textural features like contrast that depend on the intensity of the change of gray level in partial area, feature values decreased for thinned images. Especially, in the residential area, though the minimum value was around VV polarization for normal pixel spacing images, the minimum was around HH polarization for thinned images. Hence, we found differences of the pattern caused by resolution appear in the same area images, and these influence polarization properties. Textures were changed by the wave-length, we consider that was caused by the relationship between wave-length with the size and arrangement of targets.

    6. Conclusions
    In this study, the fluctuations of polarization signatures and textural features for the situation including shadow in the objective areas using high resolution PI-SAR images. For polarization signature, the value of s0 decreased relatively by including shadow, dependence on polarization was preserved. On the other hand, for textural feature, the change appeared in the polarization properties. Therefore, to analyze high resolution SAR images, the rate of shadow in objective area should be considered. For more land-cover pattern, this research is needed to advance.

    Acknowledgment
    The authors would like to thank Dr. Masaharu FUJITA, Professor of Tokyo Metropolitan Institute of Technology, Makoto SATAKE and Dr. Tatsuharu KOBAYASHI, Senior research official of Communications Research Laboratory, Ministry of Posts and Telecommunications, offered the data of PI-SAR.

    References
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    • T. Hoshi, T. Yamada, and M. Fujita: "Analysis of Textural Feature Using SIR-C Polarimetric Image Data," Trans. IEICE, Vol.J82B, No.2, pp.283~291, 1999.
    • T. Yamada and T. Hoshi: "Application of Polarization Signatures and Textural Features to Classification of Polarimetric SAR Images," Proc. NAGANO magel '99, pp.81~84, 1999.
    • T. Kobayashi, S. Uratsuka, A. Nadai, T. Umehara, M. Satake, H. Sawada, N. Mitsuzuka, G. Takao, S. Ishibashi and M. Shimada: "Forest observation by high resolution airborne dual-frequency SAR," Proc. Joint Conference of JSPRS and RSSJ, pp.563~564, 1999.
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    • Y. Yamaguchi: "Fundamentals of Polarimetric Radar and Its Applications," Realize, Inc., 1998.
    • T. Yamada and T. Hoshi: "Analysis of the surface polarization properties using high resolution airborne PI-SAR data," Proc. The 27th Conference of RSSJ, pp.163~166, 1999.
    • T. Yamada and T. Hoshi: "Investigation of the polarization properties of textural features for the high resolution airborne PI-SAR images," Proc. The 28th Conference of RSSJ, pp.43~44, 2000.
    • R. M. Haralick, K. Shanmugam, and Its'hak Dinstein: "Textural Features for Image Classification," IEEE Trans. Systems, Man, and Cybernetics, Vol.SMC3, No.6, pp.610~621, 1973.
    • T. Hashimoto and M. Matsuo: "One Method of Texture Analysis of Synthetic Aperture Radar Images," Technical Report of IEICE, Vol.IE86-88, pp.33~40, 1986.
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