Pixel Super-Resolved Lensless on-Chip Sensor with Scattering Multiplexing

Lensless on-chip microscopy has shown great potential for biomedical imaging due to its large-area and high-throughput imaging capabilities. By combining the pixel super-resolution (PSR) technique, it can improve the resolution beyond the limit of the imaging detector. However, existing PSR techniques are restricted by the feature size and crosstalk of modulation components (such as spatial light modulator), which cannot efficiently encode target information. Besides, the reconstruction algorithms suffer from the trade-off between reconstruction quality, imaging resolution, and computational efficiency. In this work, we constructed a novel integrated lensless on-chip sensor via scattering multiplexing and reported a robust PSR algorithm for target reconstruction. We employed a scattering layer to replace conventional modulators and permanently integrated it with the image detector. Benefiting from the high-degree-of-freedom calibration, the scattering layer realized fine wavefront modulation with a small feature size. Besides, the integration engineering avoided repetitious calibration and reduced the complexity of data acquisition. The reported PSR algorithm combined both model-driven and data-driven strategies, with the advantages of high fidelity, strong generalization, and low computational complexity. The remarkable performance allows it to efficiently exploit the high-frequency information from the fine modulation. A series of experiments validate that the reported sensor and PSR algorithm provide a low-cost solution for large-scale microscopic imaging, realizing ∼1.1 μm imaging resolution and ∼7 dB enhancement on the PSNR index compared to existing methods.