Autofocusing Algorithm for Pixel-Super-Resolved Lensfree On-Chip Microscopy

In recent years, lensfree on-chip microscopy has developed into a promising and powerful computational optical technique that allows for wide-field, high-throughput microscopic imaging without using any lenses. However, due to the limited pixel size of state-of-the-art image sensors, lens-free generally suffers from low resolution, which is far enough meet current demand high-resolution microscopy. Many super-resolution techniques have been solve or at least partially this problem by acquiring series low-resolution holograms with multiple lateral sub-pixel shifting axial distances. prerequisite these propagation distance each hologram can be obtained precisely, faces two major challenges. On one hand, captured inherent pixelated making it difficult determine focal plane evaluating sharpness accurately. other twin-image superimposed on backpropagated raw hologram, further exacerbating difficulties in accurate determination. study, we proposed high-precision autofocusing algorithm multi-height pixel-super-resolved Our approach consists steps: individual preliminary estimation global precise estimation. First, an improved critical function combines differential frequency domain obtain focus distances different holograms. Then, determined offset averaged, low-noise reconstruction all Simulations experimental results verified validity effectiveness algorithm.