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

机译：不同相位偏移的相位提取的并行高级迭代算法

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摘要

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 x speedup comparing with the sequential implementation on a single-core-CPU, and 10 x 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 x 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.
机译：相位提取在各种光学计量领域中是重要的，对于该领域，已经开发了许多相移算法。其中，通过迭代地估计相位和相移，高级迭代算法（AIA）可以从带有随机未知相移的条纹图案精确提取相位。然而，这些迭代使得AIA比传统的相移算法慢得多。当像素数和帧编号都很大时，此问题对于高分辨率和准确性都是大的，限制AIA的广泛应用程序。本文基于对算法结构的详细分析，第一次提出了一种完全并行化的基于GPU的AIA（Gaia）。在不划足相位提取精度的情况下，与单核-CPU上的顺序实现相比，Gaia实现了500倍的加速，以及与具有潜在收敛问题的最先进的部分GPU实现相比，10 x加速。此外，首次使用普通的NVIDIA RTX 2080 Ti GPU来实现与AIA的实时相萃取，即，所提出的Gaia仅需要26.55ms以从带2048×2048像素的13帧提取阶段。每帧。最后，通过对盖亚的实施和测试，发现增加帧数对速度性能几乎没有影响，这与我们的直接相比。因此，更多帧可用于GaIa，以增加相位提取精度，随着速度的影响很小。

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