Mesh refinement method for multi-view stereo with unary operations

3D reconstruction is an important part of digital city, high-accuracy 3D modeling method has been widely studied as an important pathway to visualizing 3D city scenes. However, the problems of image resolution, noise, and occlusion result in low quality and smooth features in the mesh model. Therefore, the model needs to be refined to improve the mesh quality and enhance the visual effect. This paper proposes a mesh refinement algorithm to fine-tune the vertices of the mesh and constrain their evolution direction on the normal vector, reducing their freedom degrees to one. The evolution of vertices only involves one motion distance parameter on the normal vector, simplifying the complexity of the energy function derivation. Meanwhile, Gaussian curvature is used as a regularization term, which is anisotropic and preserves the edge features during the reconstruction process. The mesh refinement algorithm with unary operations fully utilizes the original image information and effectively enriches the local detail features of the mesh model. This paper utilizes five public datasets to conduct comparative experiments, and the experimental results show that the proposed algorithm can better restore the detailed features of the model and has a better refinement effect in the same number of iterations compared with OpenMVS library refinement algorithm. At the same time, in the comparison of refinement results with fewer iterations, the algorithm in this paper can achieve more desirable results.