Abstract

The use of multiple diverse measurements can make lensless phase retrieval more robust. Conventional diversity functions include aperture diversity, wavelength diversity, translational diversity, and defocus diversity. Here we discuss a lensless imaging scheme that employs multiple spherical-wave illuminations from a light-emitting diode array as diversity functions. In this scheme, we place a binary mask between the sample and the detector for imposing support constraints for the phase retrieval process. This support constraint enforces the light field to be zero at certain locations and is similar to the aperture constraint in Fourier ptychographic microscopy. We use a self-calibration algorithm to correct the misalignment of the binary mask. The efficacy of the proposed scheme is first demonstrated by simulations where we evaluate the reconstruction quality using mean square error and structural similarity index. The scheme is then experimentally tested by recovering images of a resolution target and biological samples. The proposed scheme may provide new insights for developing compact and large field-of-view lensless imaging platforms. The use of the binary mask can also be combined with other diversity functions for better constraining the phase retrieval solution space. We provide the open-source implementation code for the broad research community.

Highlights

  • Common image recording devices are generally incapable of recording phase information of the incoming light waves

  • The efficacy of the proposed scheme is first demonstrated by simulations where we evaluate the quality of the reconstruction using mean square error (MSE) and structural similarity index (SSIM)

  • The scheme is experimentally demonstrated by recovering images of a resolution target and biological samples

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Summary

INTRODUCTION

Inspired by the configuration of Fourier ptychographic microscopy (FPM),[23] here we discuss a lensless imaging implementation that employs a binary mask as a support constraint and uses multiple spherical wave illuminations as diversity functions. The binary mask in the lensless scheme enforces the light field to be zeros at certain locations in a controllable manner, and it is similar to the Fourier aperture constraint in FPM. We use a self-calibration algorithm to correct the misalignment of the binary mask and such a correction process is similar to the pupil recovery scheme in FPM.[24] The efficacy of the proposed scheme is first demonstrated by simulations where we evaluate the quality of the reconstruction using mean square error (MSE) and structural similarity index (SSIM). We will summarize the results and discuss the future directions, including sub-pixel implementation, multi-state modeling, and the optimal design of the binary mask

IMAGING MODEL AND RECONSTRUCTION PROCESS
Forward imaging model
Image reconstruction with a known mask
Image reconstruction with mask updating
SIMULATIONS
SUMMARY AND DISCUSSION

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