Adaptive Complex-Amplitude Texture Classifier that Deals with Both Height and Reflectance for Interferometric SAR Images(Special Issue on Problems of Random Scattering and Electromagnetic Wave Sensing)
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概要
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We propose an adaptive complex-amplitude texture classifier that takes into consideration height as well as reflection statistics of interferometric synthetic aperture radar(SAR) images. The classifier utilizes the phase information to segment the images. The system consists of a two-stage preprocessor and a complex-valued SOFM. The preprocessor extracts a complex-valued feature vectors corresponding to height and reflectance statistics of blocks in the image. The following SOFM generates a set of templates(references)adaptively and classifies a block into one of the classes represented by the templates. Experiment demonstrates that the system segments an interferometric SAR image successfully into a lake, a mountain, and so on. The performance is better than that of a conventional system dealing only with the amplitude information.
- 社団法人電子情報通信学会の論文
- 2000-12-25
著者
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Hirose A
Univ. Tokyo Tokyo Jpn
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HIROSE Akira
Institute of Prysics,Univesity of Tsukiba
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SUKSMONO Andriyan
Research Center for Advanced Science and Technology(RCAST), The University of Tokyo
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HIROSE Akira
Research Center for Advanced Science and Technology(RCAST), The University of Tokyo
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Hirose Akira
Research Center For Advanced Science & Technology University Of Tokyo:dept.of Frontier Informati
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Suksmono A
Inst. Teknologi Bandung Bandung Idn
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