Adaptive lens-free computational coherent imaging using autofocusing quantification with speckle illumination

Area of Science:

• Optical Imaging
• Biomedical Engineering
• Computational Imaging

Background:

• Lensfree imaging offers compact, aberration-free biological imaging.
• Multi-distance phase retrieval (MDPR) is a key technique but sensitive to distance measurement errors.
• Existing auto-focusing methods for MDPR are prone to noise and artifacts.

Purpose of the Study:

• To develop a stable and robust auto-focusing scheme for lensfree multi-distance phase retrieval.
• To overcome the limitations of noise sensitivity and heavy workload in traditional MDPR.
• To enhance the imaging quality and reliability of lensfree biological imaging systems.

Main Methods:

• An adaptive imaging scheme incorporating a diffuser into the lensfree system was proposed.
• Speckle imaging combined with a sharpness quantification function was used to find the optimal sample-to-sensor distance.
• Intensity patterns under coherent illumination were utilized for in-focus image reconstruction.

Main Results:

• The proposed method demonstrated enhanced stability and robustness in auto-focusing.
• Experiments confirmed improved imaging resolution and effective optical sectioning.
• The speckle-based auxiliary significantly reduced sensitivity to noise and artifacts.

Conclusions:

• The novel adaptive imaging scheme provides a simple, stable, and robust tool for auto-focusing in lensfree imaging.
• This method enhances the practical applicability of multi-distance phase retrieval for biological applications.
• The integration of a diffuser offers a significant advancement in lensfree microscopy auto-focusing.