🤖 AI Summary
Existing sub-meter lunar digital elevation models (DEMs) suffer from insufficient detail due to limitations in stereo imaging baselines. This study addresses this constraint by proposing a novel framework that treats shape-from-shading (SfS) as an independent source of topographic information, leveraging high-resolution imagery from the Chang’e-2 Orbiter High-Resolution Camera (OHRC) to refine DEMs without relying on stereo constraints. Through a three-stage smoothness-weight parameter sweep and systematic sensitivity analysis, the method significantly improves the statistical accuracy of surface slope estimates, reveals previously unresolved fine-scale crater morphologies, and elucidates the spatially variable impact of large incidence angle differences and local image coverage on enhancement quality.
📝 Abstract
This study presents a Shape from Shading (SfS) framework to enhance sub-metre resolution lunar digital elevation models (DEMs) using imagery from the Orbiter High Resolution Camera (OHRC) aboard Chandrayaan-2. The framework applies SfS to an independent OHRC image of the same region, enabling SfS not just as a refinement tool, but as a source of new topographic data, unconstrained by stereo baseline limitations. The method is applied across three lunar sites, including the Cyrillus crater, the Vikram landing region, and the lunar south pole (Mons Mouton), with a systematic three-stage parameter sweep on the SfS smoothness weight. Results show measurable topographic enhancement, particularly in surface slope statistics, revealing fine-scale crater morphology previously unresolved. A limiting case is also characterized, where large pitch angle separation between the shading image and stereo pair reduces SfS sensitivity, and partial footprint coverage of the shading image is identified as a factor influencing spatially variable enhancement quality.