Fusion of SAR intensity and coherence data in a Markov random field model for line extraction

An approach to automatic line extraction is proposed where synthetic aperture radar (SAR) intensity is combined with interferometric coherence. The information fusion is based on Bayesian statistics and part of a Markov random field (MRF) model for line extraction. Both intensity and coherence data are evaluated using rotating templates. The different statistical properties of intensity and coherence are taken into account by a multiplicative noise model and an additive noise model, respectively. The MRF model introduces prior knowledge about the continuity and the narrowness of lines. The approach is demonstrated using a satellite borne ERS tandem data set