This article presents a technique of fusing point clouds from multiple view angles generated using synthetic aperture radar (SAR) tomography. Using TerraSAR-X high resolution spotlight data stacks, one such point has a population of about 2×107 points, with a density of around 106 points / km2. Such large point population leads to a high computational cost while doing the fusion in 3D space. Therefore, we introduce a feature-based unsupervised technique for point clouds fusion by detecting and matching building contour end points and aligning flat roofs in the two point clouds. The same idea can also be exploited as a general way to evaluate the fusion accuracy of other fusion techniques.     «

This article presents a technique of fusing point clouds from multiple view angles generated using synthetic aperture radar (SAR) tomography. Using TerraSAR-X high resolution spotlight data stacks, one such point has a population of about 2×107 points, with a density of around 106 points / km2. Such large point population leads to a high computational cost while doing the fusion in 3D space. Therefore, we introduce a feature-based unsupervised technique for point clouds fusion by detecting and m...     »