Lensfree auto-focusing imaging with coarse-to-fine tuning method

• Published in: Optics and lasers in engineering Vol. 181; p. 108366
• Main Authors: Ding, Zhihui, Zheng, Shenghao, Zhang, Feilong, Li, Qiang, Guo, Cheng
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2024
• Subjects: Auto-focusing; Deep learning; Lensfree imaging; Deep learning; Lensfree imaging; Auto-focusing
• ISSN: 0143-8166; 1873-0302
• DOI: 10.1016/j.optlaseng.2024.108366

We propose a coarse-to-fine tuning method to realize fast and robust lensfree auto-focusing imaging. Its highlight can be generalized as:•A coarse-to-fine tuning method is proposed to realize fast and robust diffractive distance estimation for lensfree on-chip microscopy.•In the coarse tuning, a simulation-driven network (sFocusNet) is proposed to acquire the coarse searching range.•In the fine tuning, a new sharpness metric, named as regularization of gradient (RoG), is constructed to obtain the final distance within the coarse searching range.•In experiment, 23 sets of samples are used to demonstrate the superiority and generalization of our method. Sample-to-sensor distance is a crucial predefined parameter for lensfree on-chip microscopes. Inaccurate estimation of the distance could lead to a failure of high-frequency detail recovery. To address it, conventional methods either evaluate the sharpness of back-propagated Z-stack holograms or adopt a pretrained end-to-end classification neural network. However, fast and robust distance estimation is still a challenging task. Here we propose a coarse-to-fine auto-focusing method to achieve fast and robust distance estimation for lensfree on-chip microscopy. In our method, a simulation-driven focus network (sFocusNet) is designed as a coarse tuning to decrease the distance searching range, and then a regularization of gradient (RoG) metric is constructed as a fine tuning to achieve an accurate estimation. Experimental results of different samples are given to verify the superiority and generalization of our method. We believe that our method will offer a practical auto-focusing solution for the commercialization of lensfree microscopes.