Differentiable pixel-super-resolution lensless imaging

Conventional lensless imaging systems require complex phase diversity measurements and sequential processing steps, limiting their practical application despite their compact design. We present a differentiable end-to-end pixel-super-resolution (dPSR) technique that unifies PSR hologram synthesis, autofocusing, and complex-field reconstruction within a single optimization framework. By jointly optimizing these traditionally separate processes, our method eliminates both phase diversity requirements and error accumulation from sequential processing. Our method achieves superior position estimation accuracy (mean error 0.0282 pixels versus 0.1172 pixels with conventional methods), delivering precise autofocusing with accuracy better than 0.3 µm, and enabling a twofold resolution enhancement beyond the sensor’s native pixel size. This robust performance is validated through both simulated and experimental results, including challenging phase objects and label-free cell imaging, establishing dPSR as a practical solution for high-resolution microscopy applications.