Single-shot lensless masked imaging with enhanced self-calibrated phase retrieval

Area of Science:

• Optics and Photonics
• Computational Imaging
• Wavefront Sensing

Background:

• Single-shot lensless imaging offers low-cost, miniaturized wave field recovery using binary amplitude masks.
• However, partial wave field capture leads to ill-posed inverse problems in decoding.
• Existing methods struggle with robustness and flexibility in complex imaging scenarios.

Purpose of the Study:

• To develop an enhanced self-calibrated phase retrieval (eSCPR) method for single-shot lensless imaging.
• To achieve joint recovery of the binary amplitude mask distribution and the sample's wavefront.
• To improve the robustness and flexibility of wave field recovery in lensless imaging systems.

Main Methods:

• Proposed an enhanced self-calibrated phase retrieval (eSCPR) approach.
• Developed a sparse regularized phase retrieval (SrPR) algorithm for mask distribution calibration.
• Implemented a denoising regularized phase retrieval (DrPR) algorithm for sample wavefront reconstruction.

Main Results:

• Successfully demonstrated joint recovery of mask distribution and sample wavefront in a single shot.
• Achieved robust and flexible image recovery compared to conventional single-shot methods.
• Validated the method's superiority through experimental results with diverse samples.

Conclusions:

• The eSCPR method effectively addresses the ill-posed nature of single-shot lensless imaging.
• This approach offers a significant advancement in low-cost, miniaturized optical imaging systems.
• The proposed technique shows broad applicability for various sample imaging and wavefront recovery tasks.