A Mismatch Removal Method Based on Global Constraint and Local Geometry Preservation for Lunar Orbiter Images

Abstract

Mismatch removal is a crucial step in multi-view matching of lunar orbiter images. This process involves complex challenges like terrain-induced distortion and non-unique geometric structures due to repetitive textures. Traditional methods, whether global constraints or local constraints, fall short in adequately addressing these issues in orbiter imagery. Therefore, this paper proposes an effective method for mismatch removal of orbiter images based on global constraint and local geometry preservation combined with the imaging model. In this method, a clean neighborhood of each matching point based on the characteristic of centralized distribution of the backprojection residuals globally is constructed. In the local region, we define a local minimum geometric polygon consisting of the center feature point and its three neighbors, and combine the similarity of the back-projection difference vectors with the affine invariance of the polygon to distinguish the correct matches and mismatches by measuring the degree of local geometry preservation. A series of experiments encompassing parameter sensitivity analysis, comparison studies and ablation experiments were conducted on the Lunar Reconnaissance Orbiter image datasets to demonstrate the effectiveness and reliability of the proposed method. The results indicate that our method exhibits a notable insensitivity to parameter variations, and outperforms other advanced methods in both qualitative and quantitative evaluations. Moreover, a large-scale orbiter images multi-view matching tie points extraction framework is extended based on the proposed mismatch removal method, which can achieve better results than commonly used photogrammetric software in terms of the number and accuracy of tie points.