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Sub-Diffraction Visible Imaging Using Macroscopic Fourier Ptychography and Regularization by Denoising

机译:亚衍射可见光成像,使用傅里叶宏观傅里叶分型和通过降噪进行正则化

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Imaging past the diffraction limit is of significance to an optical system. Fourier ptychography (FP) is a novel coherent imaging technique that can achieve this goal and it is widely used in microscopic imaging. Most phase retrieval algorithms for FP reconstruction are based on Gaussian measurements which cannot extend straightforwardly to long range, sub-diffraction imaging setup because of laser speckle noise corruption. In this work, a new FP reconstruction framework is proposed for macroscopic visible imaging. When compared with existing research, the reweighted amplitude flow algorithm is adopted for better signal modeling, and the Regularization by Denoising (RED) scheme is introduced to reduce the effects of speckle. Experiments demonstrate that the proposed method can obtain state-of-the-art recovered results on both visual and quantitative metrics without increasing computation cost, and it is flexible for real imaging applications.
机译:超过衍射极限的成像对光学系统很重要。傅里叶刻印术(FP)是一种可以实现该目标的新颖相干成像技术,它已广泛用于显微成像。大多数用于FP重建的相位检索算法都是基于高斯测量的,由于激光散斑噪声的破坏,该测量不能直接扩展到远距离亚衍射成像设置。在这项工作中,提出了一种用于宏观可见光成像的新的FP重建框架。与现有研究相比,采用重加权振幅流算法进行更好的信号建模,并引入了降噪正则化(RED)方案以减少斑点的影响。实验表明,该方法可以在视觉和定量指标上获得最新的恢复结果,而不会增加计算成本,并且对于实际的成像应用具有灵活性。

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