3D Reconstruction Method of Space Target on Optical Images with Wide Baseline via Neural Radiance Field

Abstract

3D reconstruction of space targets using optical measurement data is an important topic in the field of space surveillance and spacecraft service in orbit. The core of current mainstream 3D reconstruction methods is to establish feature association between optical images. In space-based optical imaging scenes, the texture of target region is missing and the range of view is large, which causes great difficulties in feature extraction and matching of image sequences. Neural radiance field technology does not need to extract explicit features, and its implicit expression of 3D scenes has great potential for solving reconstruction problems in weak texture and broad baseline cases. Therefore, a novel 3D reconstruction method for a sequence of images based on neural radiance field is proposed. The proposed method breaks through the limitation of traditional 3D reconstruction methods which rely on rich texture and narrow baseline image sequences. Simulation experiments show that compared with the existing methods for space target images with weak texture and wide baseline, our method performs better in terms of accuracy and completeness.