Edge Constrained DSM Refinement Based on Shading From High-Resolution Multiview Satellite Images

Surface refinement with shading information is a popular approach to recover fine details from the initial surfaces reconstructed from multiview stereo (MVS) methods. However, the existence of discontinuity areas challenges these methods in urban scenes. To address this need, this article proposes an edge constrained digital surface model (DSM) refinement method based on shading from high resolution multiview satellite images. The proposed method combines the advantages of stereo matching and shape from shading techniques. First, an improved semiglobal matching (SGM) method is applied to reconstruct the initial DSM; then, the initial DSM and the original images are used to detect the discontinuity areas in the scene; finally, the initial DSM is refined by minimizing an edge constrained energy function, which models the imaging process with the illumination, surface albedo, and surface normal. Experiments with Pleiades and GaoFen-7 satellite images show that the proposed method can recover the detailed geometry structures well and achieve an improvement of elevation accuracy up to 18.4%, 12.95%, 56.94%, 59.02%, compared to the initial DSM, the recently published shading-based DSM reconstruction method and two commercial software solutions (SURE and Metashape), respectively.