Control Network Construction for LRO NAC Images Based on Refining Tie Points by Matching With Shaded LOLA DEM

The upcoming exploration activities in the lunar south pole require high-resolution mapping products to support landing site selection and navigation. The special terrain and illumination conditions in the lunar south pole pose significant challenges to photogrammetric processing. Existing lunar mapping products exhibit limited coverage and accuracy in the south pole region and cannot meet the exploration missions' requirements. In this study, a new control network construction method is proposed based on refining tie points by image matching between the approximate orthophotos of Lunar Reconnaissance Orbiter (LRO) Narrow-Angle Camera (NAC) images and shaded digital elevation model (DEM) maps. The shaded DEM maps are generated using Lunar Orbiter Laser Altimeter (LOLA) terrain models with the same acquisition time of on-orbit NAC images, making them have very similar illumination conditions to the on-orbit images. Using the shaded DEM maps as a transition, we establish the coordinate transformation relationship between the stereopairs of NAC images by computing the homograph transformation matrix in orthophoto space. Then, the candidate control measures in the control network are refined in orthophoto space and then converted to the original image space. We conducted experiments using two sets of NAC images near the lunar south pole. The experimental results demonstrate that the proposed method can effectively solve the problems of image matching and control network generation for lunar south pole images.