Regularization and completion of tomosar point clouds in a projected height map domain

TomoSAR (Tomographic SAR) is a technique allowing to extend SAR imaging to the third dimension by using several images of a scene acquired from different sensor positions. 3D point clouds extracted thanks to tomographic processing methods are often corrupted by noise and artifacts which need to be corrected. In this paper, we propose a simple convex optimization formulation that exploits the geometric constraint that the line of sight between a sensor and a surface measurement must be unobscured. We demonstrate the ability of our method to denoise point clouds and fill holes on both synthetic and experimental DLR E-SAR data.