Adaptive-window angular spectrum algorithm for near-field ptychography

摄影术 光学 角谱法 算法 物理 计算 傅里叶变换 卷积(计算机科学) 衍射 计算机科学 探测器 视野 相位恢复 人工智能 人工神经网络 量子力学
作者
An Pan,Meiling Zhou,Yan Zhang,Junwei Min,Ming Lei,Baoli Yao
出处
期刊:Optics Communications [Elsevier]
卷期号:430: 73-82 被引量:19
标识
DOI:10.1016/j.optcom.2018.08.035
摘要

Near-field ptychography provides advantages over far-field ptychography that large field-of-view (FOV) can be imaged with fewer diffraction images, and with weaker requirements on the detector dynamic range and beam coherence, which has drawn attention recently. However, the propagation distance of traditional angular spectrum (AS) method is limited and the reconstruction of the smallest resolvable object detail is restricted by the sensor's pixel size. To this end, we propose an adaptive-window angular spectrum (AWAS) algorithm to solve both problems by adding the window adaptively associated with the propagation distance and avoid the extra computations via extra scaling factors. Meanwhile, it features validity for the independent sample size and the sample number on the observation plane. This algorithm is strictly deduced from the Rayleigh–Sommerfeld formula and based on the linear convolution, which can be evaluated by fast Fourier transform effectively. The burden of calculations is comparable to traditional AS method. The performance has been achieved both in two-dimensional and three-dimensional near-field ptychography with simulations and experiments. This method will make near-field ptychography more practical and can be used in X-ray or electron-microscopy and other computational imaging techniques.

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