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

摘要

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 prepro- cessor and a complex-valued SOFM. The preprocessor extracts a complex-valued feature vectors corresponding the height and re- flectance statistics of blocks in the image.