A MULTI-VIEW IMAGE MATCHING METHOD FOR FEATURE POINTS BASED ON THE MOVING Z-PLANE CONSTRAINT

Abstract

Focusing on the serious occlusion problem in city images, this paper makes full use of the advantage of multi-view image matching, and proposes a reliable multi-view image matching method based on the moving Z-Plane constraint. It supposes a fictitious plane in the object space, and the plane is divided to regular grid cell (small plane element) by a certain interval (≥ image resolution). By moving the plane to different elevation positions, this algorithm makes feature point projection ray in overall images intersect with the plane, and constrains the candidate points by grid cells in the plane. Feature points which come from different images projection ray in the same grid cell on the plane may be regarded as the matching candidates. It selects the images which matching candidate points by gray similarity constraint to avoid the effect from occlusion image. According to the number of projection ray in the grid cell, this algorithm adopts hierarchy matching strategy of "the best candidate will be matched in the first instant", and uses initial matching results as constraint condition in the latter matching process. Finally, the validity of the algorithm proposed in this paper is verified by the experiments using four UltraCamX (UCX) digital aerial images and the algorithm is shown to have reliable matching results.