Opt Express. 2020 Nov 23;28(24):35438-35453. doi: 10.1364/OE.403780.
Fourier Ptychographic Microscopy (FPM) allows high resolution imaging using iterative phase retrieval to recover an estimate of the complex object from a series of images captured under oblique illumination. FPM is particularly sensitive to noise and uncorrected background signals as it relies on combining information from brightfield and noisy darkfield (DF) images. In this article we consider the impact of different noise sources in FPM and show that inadequate removal of the DF background signal and associated noise are the predominant cause of artefacts in reconstructed images. We propose a simple solution to FPM background correction and denoising that outperforms existing methods in terms of image quality, speed and simplicity, whilst maintaining high spatial resolution and sharpness of the reconstructed image. Our method takes advantage of the data redundancy in real space within the acquired dataset to boost the signal-to-background ratio in the captured DF images, before optimally suppressing background signal. By incorporating differentially denoised images within the classic FPM iterative phase retrieval algorithm, we show that it is possible to achieve efficient removal of background artefacts without suppression of high frequency information. The method is tested using simulated data and experimental images of thin blood films, bone marrow and liver tissue sections. Our approach is non-parametric, requires no prior knowledge of the noise distribution and can be directly applied to other hardware platforms and reconstruction algorithms making it widely applicable in FPM.
傅里叶叠层相位显微术（FPM）通过迭代相位恢复允许高分辨率成像，从一系列在斜照明下捕获的图像中恢复对复杂物体的估计。FPM 特别容易受到噪声和未校正背景信号的影响，因为它依赖于从明场和噪声暗场（DF）图像中组合信息。在本文中，我们考虑了 FPM 中的不同噪声源的影响，并表明，DF 背景信号和相关噪声的去除不足是重建图像中伪影的主要原因。我们提出了一种简单的 FPM 背景校正和去噪方法，该方法在图像质量、速度和简单性方面优于现有方法，同时保持了重建图像的高空间分辨率和清晰度。我们的方法利用了采集数据集内实空间中的数据冗余性，在最优抑制背景信号之前，提高了捕获的 DF 图像中的信号与背景比。通过在经典 FPM 迭代相位恢复算法中合并差分去噪图像，我们表明可以在不抑制高频信息的情况下有效地去除背景伪影。该方法使用模拟数据和薄血膜、骨髓和肝组织切片的实验图像进行了测试。我们的方法是非参数的，不需要噪声分布的先验知识，并且可以直接应用于其他硬件平台和重建算法，使其在 FPM 中广泛适用。
