Fixed window aggregation AD-census algorithm for phase-based stereo matching

Phase-based stereo matching (PSM) is a vital step in binocular structured light. PSM is hard to strike a balance between efficiency and accuracy, especially because of the absolute phase matrix’s (APM) double data type. It means that PSM needs more run time and memory than conventional intensity images’ stereo matching. In this paper, we propose a modified absolute difference (AD)-Census algorithm called the fixed window aggregation AD-Census (FWA-AD-Census) to balance the contradiction between efficiency and accuracy in PSM. The FWA-AD-Census aggregates matching cost in a fixed support window instead of an adaptive support window in AD-Census. We analyze the reason why PSM is more suitable to aggregate the matching cost in a fixed support window. Simulations and experiments are conducted to verify the FWA-AD-Census’s performances by comparing the FWA-AD-Census with two other local stereo matching algorithms. One is the AD-Census, which is more accurate but less efficient. Its matching cost is aggregated in an adaptive support window. Another is the sum of absolute difference (SAD), which is more efficient but less accurate, and its matching cost is aggregated in a fixed support window. Theoretical analysis and experimental results both indicate that the proposed algorithm can achieve similar accuracy to the AD-Census with less run time.