Improving Lunar Topography with Deep Learning Schrödinger Bridges

2026-06-12

AI Summary

This study addresses the high computational cost and limited scalability of existing planetary terrain super-resolution methods, which hinder fine-grained analysis of lunar surface processes. The authors propose a novel diffusion-based generative model that incorporates the Schrödinger bridge framework into planetary terrain reconstruction for the first time. By integrating optical imagery at the target resolution as a physical constraint, the method achieves efficient, scalable, and high-fidelity terrain super-resolution. Combining Shape-from-Shading principles with generative modeling, the approach not only significantly improves reconstruction quality but also provides pixel-level uncertainty quantification. Experiments on simulated narrow-angle camera data from lunar orbiters demonstrate the method’s flexibility, scalability, and practical utility.

Abstract

Increasing the resolution of planetary topography models can enable a better understanding of surface processes and geomorphology; however, existing analytical super-resolution methods are expensive and difficult to apply at large scales. Generative models provide the tools to learn complex relationships within data and can be applied at scale due to hardware accelerators and parallelization. We present a diffusion-based Schrödinger Bridge (SB) generative modeling approach for lunar topography super-resolution, connecting the distribution of low-resolution topography to that of high-resolution topography, incorporating physically-constraining optical imagery. Our approach is inspired by existing Shape-from-Shading methods, which improve a priori low-resolution topography by using optical images at the target resolution. We train SBs on a novel dataset of rendered lunar topography, emulating optical imagery from the Lunar Reconnaissance Orbiter Narrow Angle Camera. The result is a flexible approach for topography super-resolution which can provide pixel-level uncertainties in the reconstruction.

Problem

• lunar topography
• super-resolution
• planetary surface
• geomorphology
• high-resolution modeling

Innovation

• Schrödinger Bridge
• topography super-resolution
• diffusion generative model
• Shape-from-Shading
• lunar remote sensing