Abstract

Lunar Digital Elevation Model (DEM) is important for lunar successful landing and exploration missions. Lunar DEMs are typically generated by photogrammetry or laser altimetry approaches. Photogrammetric methods require multiple stereo images of the region of interest and it may not be applicable in cases where stereo coverage is not available. In contrast, reflectance based shape reconstruction techniques, such as shape from shading (SfS) and shape and albedo from shading (SAfS), apply monocular images to generate DEMs with pixel-level resolution. We present a novel hierarchical SAfS method that refines a lower-resolution DEM to pixel-level resolution given a monocular image with known light source. We also estimate the corresponding pixel-wise albedo map in the process and based on that to regularize the shape reconstruction with pixel-level resolution based on the low-resolution DEM. In this study, a Lunar–Lambertian reflectance model is applied to estimate the albedo map. Experiments were carried out using monocular images from the Lunar Reconnaissance Orbiter Narrow Angle Camera (LRO NAC), with spatial resolution of 0.5–1.5m per pixel, constrained by the Selenological and Engineering Explorer and LRO Elevation Model (SLDEM), with spatial resolution of 60m. The results indicate that local details are well recovered by the proposed algorithm with plausible albedo estimation. The low-frequency topographic consistency depends on the quality of low-resolution DEM and the resolution difference between the image and the low-resolution DEM.

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