Outer Space Experiences in Virtual Reality: Towards Diffusion Models for Extraterrestrial Terrain Reconstruction

Virtual Reality representations of distant planets, stars, and galaxies are a driving factor for research, scientific dissemination, and public outreach. Immersive environments can be used to train astronauts, plan future missions, or study planetary features. Moreover, the dissemination of these endeavors through exhibits in museums and planetariums makes it possible to effectively communicate the latest research findings to a wider audience. To correctly visualize outer space, in particular the surfaces of celestial bodies, virtual environments must rely on scientifically accurate datasets derived from telescopes and spacecraft, which often present missing or degraded values. The current work analyzes the processing pipeline for extraterrestrial terrain data representation in VR, highlighting the most frequent errors that result in data degradation, along with their negative impacts on visualization and usability. The current work presents an approach for restoring missing terrain data using generative diffusion models. Results show visually consistent 3D reconstructions, suitable for representation in Virtual Reality, also supported by positive preliminary quantitative assessments (39.4495 in PSNR and 0.9660 in SSIM).