The use of disparity information is computationally costeffective for 3D-assisted mapping applications. However, off-nadir satellite images over dense urban areas suffer from severe occlusion. Therefore, large gaps will be created due to the unsuccessful matching in the occluded areas. Commonly, gap interpolation produces misleading information that destroys the quality of the subsequent information extraction application. Hence, the more reliable solution is to fill the occlusion gaps by supplementary data. However, disparity maps are the co-relation of one stereo pair. Hence, supplementary disparity maps cannot be directly generated and applied. Thus, this paper introduces the Double Projection Plane (DPP) method for constructing disparity proportionality among multi-view stereo satellite images and calculating analytically the transferring scales required for producing supplementary disparity data. Accordingly, based on multi-view stereo satellite images, this method is promising to provide gap- and-outlier-free disparity maps that have the potential to replace the need for elevation models to some extent.
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