AI 中文总结
研究无透镜成像中空间相干性作用，用相干感知正向模型，在有效源空间相干长度可控范围生成模拟测量数据并重建，发现降低空间相干性会降质重建，考虑部分相干性可提升质量，为系统优化提供途径。
AI 中文摘要
无透镜成像技术通过计算从无成像光学元件记录的衍射图案中恢复物体信息，其性能强烈依赖于图像重建过程中使用的正向模型。即使实际照明呈现部分空间相干性，重建误差的一个常见来源是完全相干传播的假设。本文使用基于广义范西特 - 泽尼克 - 谢尔传播的相干感知正向模型，研究了各种物体类别中空间相干性的作用。在有效源空间相干长度的可控范围内生成模拟测量数据，并使用部分相干正向模型或传统相干传播模型进行重建。结果表明，在相干假设下，空间相干性降低会逐渐使重建质量下降，而考虑部分相干性可以保留物体结构并提高图像质量，特别是对于密集的高空间频率特征。实验测量的重建进一步证实了在部分空间相干照明下使用相干感知反演的实际需求。这些发现确立了空间相干性作为无透镜成像反问题的一个决定性因素，并为部分相干无透镜成像系统的优化提供了途径。
英文摘要
Lensless imaging is a technique that recovers object information computationally from diffraction patterns recorded without imaging optics, making its performance strongly dependent on the forward model used during image reconstruction. A common source of reconstruction error is the assumption of fully coherent propagation, even when the illumination exhibits partial spatial coherence in practice. Here, the role of spatial coherence is examined for assorted object classes using a coherence-aware forward model based on generalised van Cittert-Zernike Schell propagation. Simulated measurements are generated over a controlled range of effective source spatial coherence lengths and reconstructed using either a partially coherent forward model or a conventional coherent propagation model. Our results show that decreasing spatial coherence progressively degrades reconstructions under the coherent assumption, whereas incorporating partial coherence can preserve object structure and improve image quality, particularly for dense high-spatial-frequency features. Reconstructions from experimental measurements further confirm the practical need to use coherence-aware inversion under partially spatially coherent illumination. These findings establish spatial coherence as a defining component of the inverse problem in lensless imaging and provide a route to optimization of partially coherent lensless imaging systems.
CommentsMain text and supplement with 4 and 3 figures respectively
