Accurate 3D Terrain Reconstruction for Multi-View Thermal Infrared Images with Small Intersection Angles

Accurate 3D terrain reconstruction from multi-view whisk-broom thermal infrared imagery with small intersection angles remains challenging because stereo geometry is weak and height sensitivity is limited. To address this challenge, we develop an affine-initialized rational polynomial coefficient (RPC) reconstruction framework for 3D positioning under weak geometric conditions. An affine model is first used to estimate initial 3D coordinates from image tie points, which are then used to initialize RPC-based refinement. The refinement adopts an iterative scheme with hierarchical updates, where longitude and latitude are optimized before altitude to mitigate error propagation when height observability is low. The method is evaluated using multi-view data acquired by the SDGSAT-1 Thermal Infrared Spectrometer (TIS) over plain, hilly, and mountainous terrains, with intersection angles ranging from 0.57° to 6.5°. The results show that approximately 80% of the reconstruction errors fall within 2 pixels and more than 90% fall within 3 pixels, corresponding to 60 m and 90 m at the image resolution used in this study. The root-mean-square error (RMSE) remains below 0.3 pixels in plains, 1.3 pixels in hilly areas, and 1.8 pixels in mountainous areas. Overall, the proposed framework facilitates stable 3D terrain reconstruction from whisk-broom thermal infrared imagery and reduces reliance on confidential rigorous sensor models.