A new and efficient iterative approach to image matching
This paper addresses the problem of matching two images with unknown epipolar geometry. A new and efficient iterative algorithm is proposed, which is a part of the author's project on developing a robust image matching technique. The author defines a new measure of matching support, which allows less contribution and higher tolerance of deformation with respect to affine transformations from distant matches than from nearby ones. A new strategy for updating matches is developed, which only selects those matches having both high matching support and low matching ambiguity. The update strategy is different from the classical "winner-take-all", which evolves too soon and is easily stuck at a local minimum, and also from "loser-take-nothing", which is usually very slow. The proposed algorithm has been tested with two dozen image pairs of very different types of scenes, and very good results have been obtained. It works remarkably well in a scene with many repetitive patterns.