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一种改进的最小二乘解包裹算法

Improved Least Squares Unwrapping Algorithm

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摘要

针对激光散斑干涉图像在局部高密度噪声和拉线区域中,最小二乘解包裹算法存在过度平滑、迭代次数多和运行时间长等问题,提出一种新的算法。该算法基于散斑干涉图像近似服从周期性的抛物线分布的规律,首先采用两次矩阵变换,对噪声所在的坐标点进行锁定;继而利用掩模技术并结合二维离散余弦变换和Picard迭代方法,对噪声的传播进行抑制,从而获得平滑的图像。实验结果表明:激光散斑干涉测量对局部高密度噪声很敏感,经过平滑优化后,所提算法较传统最小二乘迭代算法具有更少的迭代次数和更短的计算时间,对单根拉线、单个噪声和变形干扰下的干涉测量的识别率高达96%,精度优于传统算法,具有很高的工程应用价值。

Abstract

In this paper, we propose an improved least squares unwrapping algorithm. This algorithm is aimed at solving the problems associated with smooth transition, large number of iterations, and long running time of least squares unwrapping in local high-density noise and wire-drawing regions of laser speckle interference images. This algorithm is based on the law that the speckle interference image approximately obeys the periodic parabolic distribution. First, the coordinate points where the noise is located are locked using two matrix transformations. Then use the mask technology and combine the two-dimensional discrete cosine transform and Picard iterative method to suppress the propagation of noise, so as to obtain smooth images. The experimental results show that laser speckle interferometry is very sensitive to local high-density noise. Thus, the proposed algorithm has fewer iterations and shorter calculation time during image smoothing and optimization compared with the traditional least-squares iterative algorithms. The recognition rate of interferometry under single noise and deformation interference is approximately 96%, and the accuracy is better than traditional algorithms, which has high engineering application value.

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中图分类号:TP391

DOI:10.3788/LOP57.181101

所属栏目:成像系统

基金项目:国家自然科学基金、广西创新驱动发展专项、广西自然科学基金、广西制造系统与先进制造技术重点实验室主任课题;

收稿日期:2019-12-10

修改稿日期:2020-02-24

网络出版日期:2020-09-01

作者单位    点击查看

彭国:桂林电子科技大学广西制造系统与先进制造技术重点实验, 广西 桂林 541000
李伟明:桂林电子科技大学广西制造系统与先进制造技术重点实验, 广西 桂林 541000
黄扬:桂林电子科技大学广西制造系统与先进制造技术重点实验, 广西 桂林 541000
陈艺海:桂林电子科技大学广西制造系统与先进制造技术重点实验, 广西 桂林 541000
高兴宇:桂林电子科技大学广西制造系统与先进制造技术重点实验, 广西 桂林 541000

联系人作者:高兴宇(gxy1981@guet.edu.cn)

备注:国家自然科学基金、广西创新驱动发展专项、广西自然科学基金、广西制造系统与先进制造技术重点实验室主任课题;

【1】Gao D P, Yin F L. Mask cut optimization in two-dimensional phase unwrapping [J]. IEEE Geoscience and Remote Sensing Letters. 2012, 9(3): 338-342.

【2】Kaufmann G H, Galizzi G E, Ruiz P D. Evaluation of a preconditioned conjugate-gradient algorithm for weighted least-squares unwrapping of digital speckle-pattern interferometry phase maps [J]. Applied Optics. 1998, 37(14): 3076-3084.

【3】Zappa E, Busca G. Comparison of eight unwrapping algorithms applied to Fourier-transform profilometry [J]. Optics and Lasers in Engineering. 2008, 46(2): 106-116.

【4】Huntley J M. Noise-immune phase unwrapping algorithm [J]. Applied Optics. 1989, 28(16): 3268-3270.

【5】Schajer G S, Zhang Y J, Melamed S. In-plane ESPI using an achromatic interferometer with low-coherence laser source [J]. Optics and Lasers in Engineering. 2015, 67: 116-121.

【6】Qian K M. A simple phase unwrapping approach based on filtering by windowed Fourier transform: the phase near edges [J]. Optics & Laser Technology. 2007, 39(7): 1364-1369.

【7】Lee Y, Ito Y, Tahara T, et al. Single-shot dual-wavelength phase unwrapping in parallel phase-shifting digital holography [J]. Optics Letters. 2014, 39(8): 2374-2377.

【8】Xu W, Cumming I. A region-growing algorithm for InSAR phase unwrapping [J]. IEEE Transactions on Geoscience and Remote Sensing. 1999, 37(1): 124-134.

【9】Costantini M. A novel phase unwrapping method based on network programming [J]. IEEE Transactions on Geoscience and Remote Sensing. 1998, 36(3): 813-821.

【10】Goldstein R M, Zebker H A, Werner C L. Satellite radar interferometry: two-dimensional phase unwrapping [J]. Radio Science. 1988, 23(4): 713-720.

【11】Xia H T, Montresor S, Guo R X, et al. Phase calibration unwrapping algorithm for phase data corrupted by strong decorrelation speckle noise [J]. Optics Express. 2016, 24(25): 28713-28730.

【12】Wang L F. Yan M. Weighted Kalman filter phase unwrapping algorithm based on the phase derivative variance map. Applied Mechanics, Materials[J]. 2013, 475/476: 991-995.

【13】Guo Y, Chen X T, Zhang T. Robust phase unwrapping algorithm based on least squares [J]. Optics and Lasers in Engineering. 2014, 63: 25-29.

【14】Chen B, Liu H W, Bao Z. Optimizing the data-dependent kernel under a unified kernel optimization framework [J]. Pattern Recognition. 2008, 41(6): 2107-2119.

【15】Wu J, Zhou H, Wu D, et al. Study of phase unwrapping algorithm from the undersampled phase [J]. Laser & Optoelectronics Progress. 2016, 53(5): 051003.
吴杰, 周皓, 吴丹, 等. 欠采样条件下相位解包裹算法的研究 [J]. 激光与光电子学进展. 2016, 53(5): 051003.

【16】Xu F C, Xing T W. Unwrapping algorithm with high noise immunity [J]. Laser & Optoelectronics Progress. 2011, 48(1): 011001.
徐富超, 邢廷文. 抑制大噪声的解包算法 [J]. 激光与光电子学进展. 2011, 48(1): 011001.

【17】Guo Y, Yang Z, Wu Q. Unwrapping method for local high density residual point wrapped phase [J]. Laser & Optoelectronics Progress. 2017, 54(4): 041202.
郭媛, 杨震, 吴全. 局部高密度残差点包裹相位的解包方法 [J]. 激光与光电子学进展. 2017, 54(4): 041202.

引用该论文

Peng Guo,Li Weiming,Huang Yang,Cheng Yihai,Gao Xingyu. Improved Least Squares Unwrapping Algorithm[J]. Laser & Optoelectronics Progress, 2020, 57(18): 181101

彭国,李伟明,黄扬,陈艺海,高兴宇. 一种改进的最小二乘解包裹算法[J]. 激光与光电子学进展, 2020, 57(18): 181101

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