Ganesh M. Balasubramaniam

arXiv2026

Role of Spatial Coherence in Single-Shot Lensless Image Reconstruction

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.

physics.optics↗

arXiv2026

Single-Shot Lensless Imaging with Physics Guided Genetic Programming

Lensless optical imaging eliminates the need for refractive optics, enabling compact and low-cost cameras with a large field-of-view, supporting point-of-care diagnostics and industrial monitoring. Practical deployments, however, remain constrained by ill-posed image reconstruction pipelines that require multiple measurements, careful calibration or object-specific training, thus limiting robustness and scalability. In this work, we introduce a single-shot lensless imaging framework that reconstructs complex objects from only a single recorded intensity pattern using a genetically programmed iterative algorithm. Our method couples a wave-propagation model with an adaptive meta-optimisation strategy to jointly estimate the object amplitude, object phase, and effective object-detector distance. Experiments demonstrate high-fidelity recovery of amplitude objects, including a USAF target and 2~$μ$m silicon beads on a glass slide, as well as a phase-dominant biological sample consisting of U2OS cells on a glass slide. Across multiple object types, wavelengths, and propagation distances, the same learned policy maintains high reconstruction quality with minimal retuning, indicating strong out-of-distribution generalisation. As a practical demonstration, the framework is integrated with a $β$-amyloid-based optical digital bead assay under wide field-of-view acquisition. The resulting platform combines single-shot capture, compact hardware, and accurate reconstruction of complex fields, enabling rapid, portable assays in which throughput, alignment tolerance, and cost are critical.

physics.optics↗