Orthorectification and DSM generation with ALOS-Prism data in urban areas

Abstract

In this paper different methods for deriving digital surface models (DSM) from ALOS Prism three line stereo images are generated and analyzed. The methods used are classical hierarchical stereo matching with forward intersection and two different dense stereo methods. These are digital line warping which was derived from speech recognition algorithms and semi global matching which is originating in computer vision. All these dense stereo methods need epipolar imagery as input and provide so called disparity images as output. For this in a first step the Prism images has to be transformed by pairs to epipolar geometry. For the reprojection of the disparity images to real DSMs rational polynomial coefficients - which were computed from the satellite ephemeris and attitude date - are used. Finally the DSMs generated by all these different methods are compared to a DSM derived from an Ikonos stereo image pair with a ground sampling distance of 1 m.