Image registration is a crucial step in interferometric synthetic aperature radar (InSAR) and in SAR tomography. Generally, a displacement of the sensors, e.g. due to different flight tracks,causes an image distortion that is dependent on the terrain height that is being observed. While ground truth digital elevation map (DEM) data are often available to roughly compensate this distortion, there are application scenarios where the acquisition paths are too irregular or DEMs are not available. In such cases, image registration via image processing is a suitable choice. While the SAR community prefers patch-based correlation techniques, the computer vision community has investigated the same issue from technically different points of view. In this article, we study the performance of correlation- and computer vision-based image registration techniques for the image registration problem in SAR, in particular in airborne SAR without ground truth. We show that computer vision algorithms can outperform correlation-based techniques.