AUTOMATIC-GENERATION OF HIGH-RESOLUTION URBAN ZONE DIGITAL ELEVATION MODELS

Our paper presents an automatic generation of high resolution urban di gital elevation models (DEMs) based on a highly redundant correlation process. We will discuss the difficulties of such a task by commenting on the state of the art, and we propose an approach in three main ste ps. In the first step, the image acquisition specification as image se quences leads to pairs with various base/height ratios in order to obt ain good precision and few errors due to hidden parts. In the second s tep we use various stereovision methods and we merge the results, thus attributing to each pixel the most probable and precise elevation. In the third step we automatically extract terrain-DEM and building-DEM from computed DEM in order to specifically post-process each class. Fi nally, we combine these two DEMs to generate a final DEM which present s the best continuity for ground surface, and which respects sharp bui lding discontinuities. The results obtained with an operational exampl e (including image size, difficulty of the scene) demonstrate the feas ibility of generating metric resolution urban data bases from automate d digital stereo methods.