Digital Surface Model Refinement Based on Projected Images

Abstract

Currently, the practical solution to remove the errors and artifacts in the digital surface models (DSM ) through stereo images is still manual or semiautomatic editing those affected patches. Although some degrees of semiautomation can be gained, the DSM refinement remains a labor consuming and expensive process. This paper proposes a new method to correct errors in DSM or/and refine an existing coarse DSM. The method employs the concept of projected images together with some image matching techniques to correct/ refine the affected regions in DSM. Since projected images are used, the proposed method can greatly simplify the complicated coordinate transformations and pixel resampling; therefore, the errors/artifacts in DSM can be amended more efficiently and accurately. Several experiments demonstrate the practical usefulness of the proposed method under some scenarios, and some potential improvements are also pointed out to accommodate the various needs during refining DSM.