Adaptive Complex-Amplitude Texture Classifier that Deals with Both Height and Reflectance for Interferometric SAR Images

Andriyan Bayu SUKSMONO  Akira HIROSE  

Publication
IEICE TRANSACTIONS on Electronics   Vol.E83-C    No.12    pp.1912-1916
Publication Date: 2000/12/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8516
Type of Manuscript: Special Section PAPER (Special Issue on Problems of Random Scattering and Electromagnetic Wave Sensing)
Category: SAR Interferometry and Signal Processing
Keyword: 
complex amplitude,  texture classifier,  interferometric SAR,  phase unwrapping,  

Full Text: PDF>>
Buy this Article



Summary: 
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.