Parallel advanced iterative algorithm for phase extraction with unknown phase-shifts

Abstract Phase-extraction is important in various fields of optical metrology, for which, many phase-shifting algorithms have been developed. Among them, the advanced iterative algorithm (AIA) can accurately extract phase from fringe patterns with random unknown phase-shifts by iteratively estimating the phase and phase-shifts. However, these iterations make the AIA much slower than traditional phase-shifting algorithms. This problem is severer when both the pixel number and the frame number are large for high resolution and accuracy, restricting AIA’s wide application. In this paper, based on the detailed analysis of the algorithm’s structure, a fully parallelized GPU-based AIA (gAIA) is proposed for the first time. Without scarifying the phase extraction accuracy, the gAIA achieves 500 ×  speedup comparing with the sequential implementation on a single-core-CPU, and 10 ×  speedup comparing with the state-of-the-art partial GPU implementation which has a potential convergence issue. Also, for the first time, the real-time phase extraction with AIA is achieved by using a normal NVIDIA RTX 2080 Ti GPU, i.e., the proposed gAIA only takes 26.55 ms to extract phase from 13 frames of fringe patterns with 2048  ×  2048 pixels per frame. Finally, through the implementation and testing of the gAIA, it is discovered that increasing the frame number has little effect on the speed performance, which is against our intuition. As a consequence, more frames can be used for gAIA to increase the phase extraction accuracy with little influence on the speed.