Aerospace, Vol. 12, Pages 658: LD-DEM: Latent Diffusion with Conditional Decoding for High-Precision Planetary DEM Generation from RGB Satellite Images

Aerospace doi: 10.3390/aerospace12080658

Authors:
Long Sun
Haonan Zhou
Li Yang
Dengyang Zhao
Dongping Zhang

A Digital Elevation Model (DEM) provides accurate topographic data for planetary exploration (e.g., Moon and Mars), essential for tasks like lander navigation and path planning. This study proposes the first latent diffusion-based algorithm for DEM generation, leveraging a conditional decoder to enhance reconstruction accuracy from RGB satellite images. The algorithm performs the diffusion process in the latent space and uses a conditional decoder module to enhance the decoding accuracy of the DEM latent vectors. Experimental results show that the proposed algorithm outperforms the baseline algorithm in terms of reconstruction accuracy, providing a new technical approach to efficiently reconstruct DEMs for extraterrestrial planets.

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Long Sun www.mdpi.com