傅里叶叠层成像是一种能够同时实现大视场和高分辨的成像方法, 公开发表的文献表明其空间分辨率极限由照明数值孔径和物镜数值孔径决定。为了进一步提高其分辨率, 提出了频域和空间约束傅里叶叠层重建方法: 利用传统重建算法获得的空间频谱进行频域约束, 以传统重建算法获得的图像进行空间约束; 该方法基于一个假设: 图像具有稀疏特性; 从传统重建算法获得的图像中提取所需的频域和空间约束条件, 不需要额外采集数据和硬件改进。仿真和实验结果表明: 与传统无约束重建方法相比, 提出的算法能够提高分辨率和改善对比度, 空间分辨率提高幅度高达~26%。

Fourier ptychography (FP) is an effective approach capable of imaging with both large field-of-view (FOV) and high resolution, the published works have proven that the resolution is limited by the sum of the illumination numerical aperture (NA) and the NA of the objective lens used. A spatial- and spectral-constrained FP (spFP) reconstruction algorithm was introduced to improve the spatial resolution. Unlike the typical unconstrained algorithm, the proposed algorithm incorporated both spatial- and spectral-constraints based on the additional prior information extracted from the typical FP reconstruction, and it did not need any additional hardware or captured images. The proposed approach was based on an assumption that the image was known to be sparse. Both simulation and experimental results show that the spFP reconstruction improves the spatial resolution by ～26%, and also improves the contrast and general quality of the reconstructed image.