Abstract The fringe projection profilometry (FPP) has obtained increasing popularity in the field of industrial automation, inverse engineering and graphics. Recent literature reveals that the non-ideal system point spread function (PSF) in FPP will cause phase error in the area around the discontinuous edge. Existing error reduction methods need to detect the location of all the edges accurately first, which are hard to accomplish when the camera is defocused. Meanwhile, the corrected data in the error area relies heavily on the data in its nearest unaffected area, which makes the corrected data unreliable. We prove that the non-ideal system PSF will also induce phase error in the area of surface details, and this is a problem seldom discussed in FPP. In this work, the relationships between the PSF-induced phase error and system parameters are deduced mathematically and numerically. Additionally, a deconvolution-based method is proposed to reduce the PSF-induced phase error in this paper. The proposed method can overcome the shortcomings of the existing approaches. Both simulation and experiment results show that our proposed method can reduce the Root Mean Square phase/height error by up to 4 times, and can also improve the measured 3D details significantly.

中文翻译：

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条纹投影轮廓法中非脉冲系统psf引起的相位误差分析与降低

摘要 条纹投影轮廓仪（FPP）在工业自动化、逆向工程和图形领域越来越受欢迎。最近的文献表明，FPP 中的非理想系统点扩展函数 (PSF) 会导致不连续边缘周围区域的相位误差。现有的误差减少方法需要首先准确检测所有边缘的位置，这在相机散焦时很难实现。同时，错误区的修正数据严重依赖于其最近未受影响区域的数据，这使得修正后的数据不可靠。我们证明了非理想系统 PSF 也会在表面细节区域引入相位误差，这是 FPP 中很少讨论的问题。在这项工作中，从数学上和数值上推导出 PSF 引起的相位误差和系统参数之间的关系。此外，本文提出了一种基于反卷积的方法来减少 PSF 引起的相位误差。所提出的方法可以克服现有方法的缺点。仿真和实验结果表明，我们提出的方法可以将均方根相位/高度误差降低多达 4 倍，并且还可以显着改善测量的 3D 细节。