Performance Evaluation of Semi-Global Approaches for the Dense Image Matching of Stereo Satellite Images.

In this study, the performance of semi-global methods for satellite stereo image matching was investigated. The performance of semi-global methods for the well-known Middlebury and KITTI sets has been the subject of many studies. Applications using satellite images may have different difficulties compared to close-range images. RVLSatStereo was used as the dataset. With this study, the similarities between SGM and MGM algorithms, in which areas they had difficulties and in which areas they gave good results were examined. As far as we know, the general performance evaluation of the semi-global methods has not been done with the BAD 2.0 metric in satellite images containing areas with different characteristics.