Very-high-resolution rapid 3D mapping of Oxia Planum using cascaded MOLA-HRSC-CTX-HiRISE

Overview & Synopsis

Stereo photogrammetry and/or photoclinometry have long been applied to the production of 3D imaging datasets for planetary surfaces. However, insufficient image resolution or reductions in the resultant 3D resolution, the lack of adequate stereo coverage and where available, lengthy processing time, various matching artefacts or noise effects, and unsatisfactory quality and complexity of processing, have long been significant barriers for large-area planetary 3D mapping. In this work, we demonstrate how deep learning based solutions can address the above issues using a single image and a coarse 3D reference as inputs.