CVLGOct 13, 2025

Enhancing the Quality of 3D Lunar Maps Using JAXA's Kaguya Imagery

arXiv:2510.11817v1h-index: 19SMC
Originality Synthesis-oriented
AI Analysis

This addresses the need for reliable terrain data for lunar exploration missions, but it is incremental as it focuses on noise reduction in existing imagery.

The paper tackled the problem of altitude inaccuracies in 3D lunar maps from Kaguya TC images, caused by compression artifacts, and resulted in reduced elevation noise to enhance safety for missions.

As global efforts to explore the Moon intensify, the need for high-quality 3D lunar maps becomes increasingly critical-particularly for long-distance missions such as NASA's Endurance mission concept, in which a rover aims to traverse 2,000 km across the South Pole-Aitken basin. Kaguya TC (Terrain Camera) images, though globally available at 10 m/pixel, suffer from altitude inaccuracies caused by stereo matching errors and JPEG-based compression artifacts. This paper presents a method to improve the quality of 3D maps generated from Kaguya TC images, focusing on mitigating the effects of compression-induced noise in disparity maps. We analyze the compression behavior of Kaguya TC imagery, and identify systematic disparity noise patterns, especially in darker regions. In this paper, we propose an approach to enhance 3D map quality by reducing residual noise in disparity images derived from compressed images. Our experimental results show that the proposed approach effectively reduces elevation noise, enhancing the safety and reliability of terrain data for future lunar missions.

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