Rahman Md Sadman Sakib, Ozcan Aydogan
Electrical and Computer Engineering Department, University of California, Los Angeles, CA, USA.
Bioengineering Department, University of California, Los Angeles, CA, USA.
Light Sci Appl. 2025 Jun 12;14(1):212. doi: 10.1038/s41377-025-01887-x.
Point spread function (PSF) engineering has been pivotal in the remarkable progress made in high-resolution imaging in the last decades. However, the diversity in PSF structures attainable through existing engineering methods is limited. Here, we report universal PSF engineering, demonstrating a method to synthesize an arbitrary set of spatially varying 3D PSFs between the input and output volumes of a spatially incoherent diffractive processor composed of cascaded transmissive surfaces. We rigorously analyze the PSF engineering capabilities of such diffractive processors within the diffraction limit of light and provide numerical demonstrations of unique imaging capabilities, such as snapshot 3D multispectral imaging without involving any spectral filters, axial scanning or digital reconstruction steps, which is enabled by the spatial and spectral engineering of 3D PSFs. Our framework and analysis would be important for future advancements in computational imaging, sensing, and diffractive processing of 3D optical information.
点扩散函数（PSF）工程在过去几十年高分辨率成像取得的显著进展中发挥了关键作用。然而，通过现有工程方法可实现的PSF结构的多样性是有限的。在此，我们报告通用PSF工程，展示了一种在由级联透射表面组成的空间非相干衍射处理器的输入和输出体积之间合成任意一组空间变化的3D PSF的方法。我们在光的衍射极限内严格分析了此类衍射处理器的PSF工程能力，并提供了独特成像能力的数值演示，例如无需任何光谱滤波器、轴向扫描或数字重建步骤的快照3D多光谱成像，这是由3D PSF的空间和光谱工程实现的。我们的框架和分析对于3D光学信息的计算成像、传感和衍射处理的未来进展将具有重要意义。
