Global Topology Based Image Stitching Using Hierarchical Triangulation

Most image stitching algorithms adopt intensity or gradient for similarity measurement. Unfortunately they fail when the scene exhibits periodic contents or similar contents. In this puper, we propose a novel global topology based image stitching method. Firstly, gradient and ratios of RBG are used to describe and compare feature points. In order to reduce the omission of matched points, a threshold is set to reserve all m:n (m, n are positive integer) feature matching. Then, we compute two compatible triangulations of gradient and color matched points to compare the topology similarity. Finally, we incrementally add 1:1 matching points which are topology matched and remove problematic points. We demonstrate the illustrative results by comparing and contrasting our output with other methods. The presented algorithm gives superior results in all examples.