论文标题

通过周期性加上光滑图像分解,在傅立叶ptychographic显微镜中去除边缘效应

Edge effect removal in Fourier ptychographic microscopy via periodic plus smooth image decomposition

论文作者

Pan, An, Wang, Aiye, Zheng, Junfu, Gao, Yuting, Ma, Caiwen, Yao, Baoli

论文摘要

傅立叶Ptychographic显微镜(FPM)是一种有前途的计算成像技术,具有高分辨率,视野广泛(FOV)和定量相恢复。到目前为止,已经报道了一系列可能破坏FPM图像质量的系统错误。然而,由边缘效应引起的不可察觉的伪影引起了我们的注意,并且还可能在傅立叶空间中使用横形伪像在FPM中降低相位成像的精度。我们发现,在同一子区域的重建相的精度取决于不同边缘条件的不同大小的块处理,这限制了通过FPM进行定量相测量。该伪像是由快速傅立叶变换(FFT)的Aperiodic图像扩展引起的。为了消除边缘效应并提高准确性,分别报道了两类的相反算法​​称为离散余弦变换(DCT)和完美的傅立叶变换(PFT),并进行了系统的讨论。尽管两种方法都可以在FPM中去除伪像,并且可能扩展到其他傅立叶分析技术,但PFT具有与常规FFT相当的效率。 PFT算法将相位准确性的标准偏差从0.08弧度提高到0.02个弧度。最后,我们总结并讨论了广义模型中FPM的所有报告的系统误差。

Fourier ptychographic microscopy (FPM) is a promising computational imaging technique with high resolution, wide field-of-view (FOV) and quantitative phase recovery. So far, a series of system errors that may corrupt the image quality of FPM has been reported. However, an imperceptible artifact caused by edge effect caught our attention and may also degrade the precision of phase imaging in FPM with a cross-shape artifact in the Fourier space. We found that the precision of reconstructed phase at the same subregion depends on the different sizes of block processing as a result of different edge conditions, which limits the quantitative phase measurements via FPM. And this artifact is caused by the aperiodic image extension of fast Fourier transform (FFT). Herein, to remove the edge effect and improve the accuracy, two classes of opposite algorithms termed discrete cosine transform (DCT) and perfect Fourier transform (PFT) were reported respectively and discussed systematically. Although both approaches can remove the artifacts in FPM and may be extended to other Fourier analysis techniques, PFT has a comparable efficiency to conventional FFT. The PFT algorithm improves the standard deviation of phase accuracy as a factor of 4 from 0.08 radians to 0.02 radians. Finally, we summarized and discussed all the reported system errors of FPM within a generalized model.

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