ADAPTIVE HIERARCHICAL DENSE MATCHING OF MULTI-VIEW AIRBORNE OBLIQUE IMAGERY

Abstract. Traditional single-lens vertical photogrammetry can obtain object images from the air with rare lateral information of tall buildings. Multi-view airborne photogrammetry can get rich lateral texture of buildings, while the common area-based matching for oblique images may lose efficacy because of serious geometric distortion. A hierarchical dense matching algorithm is put forward here to match two oblique airborne images of different perspectives. Based on image hierarchical strategy and matching constraints, this algorithm delivers matching results from the upper layer of the pyramid to the below and implements per-pixel dense matching in the local Delaunay triangles between the original images. Experimental results show that the algorithm can effectively overcome the geometric distortion between different perspectives and achieve pixel-level dense matching entirely based on the image space.