Compressed Sensing with off-axis frequency-shifting holography

TL;DR

This paper presents an experimental microscopy method combining compressed sensing and digital holography under off-axis and frequency-shifting conditions, enabling high-quality image reconstruction from minimal measurements.

Contribution

It introduces a novel CS-based imaging scheme for sparse gradient images in holographic microscopy, achieving accurate reconstruction from only 7% of measurements.

Findings

Successful reconstruction from 7% measurements

Demonstrated effectiveness of CS in holographic microscopy

Potential for new microscopy applications

Abstract

This work reveals an experimental microscopy acquisition scheme successfully combining Compressed Sensing (CS) and digital holography in off-axis and frequency-shifting conditions. CS is a recent data acquisition theory involving signal reconstruction from randomly undersampled measurements, exploiting the fact that most images present some compact structure and redundancy. We propose a genuine CS-based imaging scheme for sparse gradient images, acquiring a diffraction map of the optical field with holographic microscopy and recovering the signal from as little as 7% of random measurements. We report experimental results demonstrating how CS can lead to an elegant and effective way to reconstruct images, opening the door for new microscopy applications.