Accurate 3D Measurement from Two SAR Images Without Prior Knowledge of Scene

Abstract

Remote sensing using Synthetic Aperture Radar (SAR) is an indispensable technology for effective disaster management, owing to its large observation area, cloud penetrating ability and its independence from sunlight, which allow for quick observation of large disaster affected areas disregarding weather or time of the day. In particular, 3D measurement from SAR images could contribute a better understanding of the affected area and speed up decision making. Most methods require prior knowledge of the scene such as ground control points to achieve a reasonable level of 3D measurement accuracy, resulting in losing the advantage of quick observation. In this paper, we propose an accurate 3D measurement method from SAR images based on the principle of stereo vision without any prior knowledge of the scene. We demonstrate the effectiveness of our method compared with the conventional method through a set of experiments using an airborne SAR image dataset.