Zhang Wenhui, Zhang Hao, Jin Guofan
Opt Lett. 2020 Aug 15;45(16):4416-4419. doi: 10.1364/OL.393111.
As convolution-based diffraction calculation methods, Rayleigh-Sommerfeld convolution and the angular spectrum method (ASM) usually require zero padding to avoid circular convolution errors. This greatly increases the computational complexity and wastes a large amount of the sampling points. In this Letter, based on the analysis of sampling properties in the convolution process, we propose an adaptive-sampling ASM, which can adjust the sampling parameters according to the propagation distance to avoid circular convolution errors without zero padding. The sampling condition of the transfer function can be adaptively satisfied by rearranging the sampling points in the spatial frequency domain. Therefore, the computational complexity is significantly reduced, and all the sampling points are effectively used, which leads to a full utilization of the space-bandwidth product.
作为基于卷积的衍射计算方法，瑞利 - 索末菲卷积和角谱方法（ASM）通常需要进行零填充以避免循环卷积误差。这大大增加了计算复杂度并浪费了大量采样点。在本信函中，基于对卷积过程中采样特性的分析，我们提出了一种自适应采样的ASM，它可以根据传播距离调整采样参数，无需零填充即可避免循环卷积误差。通过在空间频域中重新排列采样点，可以自适应地满足传递函数的采样条件。因此，计算复杂度显著降低，并且所有采样点都得到有效利用，从而实现了空间带宽积的充分利用。
