A grouped scale-adaptive phase-based stereo matching method

Phase-based stereo matching algorithms are the state-of-the-art stereo techniques, which have the advantage of high accuracy, dense disparity map and parallel computing structure. As to the usual phase wraparound problem in the phase-based method, one way is to adopt a coarse-to-fine strategy, which is efficient but not robust; another is to exploit a scale-adaptive strategy, which is robust but inefficient. In this paper we put forward a grouped scale-adaptive strategy, which integrates the advantages of the previous two strategies into a mixture version. Computer simulation shows that this stereo matching algorithm can obtain accurate disparity estimation robustly and efficiently.