Role of Spatial Coherence in Single-Shot Lensless Image Reconstruction

Abstract

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.