Building extraction based on stereo analysis of high-resolution SAR images taken from orthogonal aspect directions

In this paper high-resolution SAR images of an urban scene are analyzed in order to infer buildings and their heights from the different layover effects in perpendicular taken views. Due to the strong dependence of the appearance of objects on the lighting and viewing direction, it is unlikely that a simple image-matching method would succeed. Instead, higher level object matching is proposed. Here, a knowledge-based approach is applied, a production system. The images are analyzed separately for the presence of certain object groups and their characteristics frequently appearing on buildings, such as salient rows, rectangular structures, or symmetries. The stereo analysis is then accomplished locally by means of productions that combine and match these image objects and infer the height. The approach is tested using real SAR data of an urban scene.