Building detection by fusion of optical and SAR features in metric resolution data

In this paper, we propose to jointly use optical and SAR features issued from satellite images with metric resolution, to deal with the problem of building detection and height retrieval. In a first part, a process - described in previous works - for building boundary extraction, is briefly exposed and illustrated on a Quickbird urban scene. In a second part, the framework of fusion with SAR data is developed. After the steps of feature projection and registration, a new method for building height estimation is proposed. This one is based on a Likelihood criterion optimization and is built on the scheme "height hypothesis - characteristic areas generation - energy minimization". Such an approach refers to the adequation between a potential building signature and the real signature, effectively present on the SAR image and defined by characteristic building areas such as layover, shadow, roof and ground/wall echo. This height retrieval process is tested on simulated and real (TerraSAR-X) data.