Interferometric lensless imaging: rank-one projections of image frequencies with speckle illuminations

TL;DR

This paper introduces a novel interferometric lensless imaging method using rank-one projections with speckle illuminations, enabling efficient spectral content acquisition and high-resolution imaging with theoretical guarantees and practical validation.

Contribution

It models lensless imaging as collecting symmetric rank-one projections of an interferometric matrix, providing a new theoretical framework and practical approach for high-resolution biological imaging.

Findings

The method captures up to O(Q^2) image frequencies with a multicore fiber.

Theoretical analysis shows the sensing scheme satisfies restricted isometry properties.

Experimental results validate the imaging approach on real MCF systems.

Abstract

Lensless illumination single-pixel imaging with a multicore fiber (MCF) is a computational imaging technique that enables potential endoscopic observations of biological samples at cellular scale. In this work, we show that this technique is tantamount to collecting multiple symmetric rank-one projections (SROP) of an interferometric matrix--a matrix encoding the spectral content of the sample image. In this model, each SROP is induced by the complex sketching vector shaping the incident light wavefront with a spatial light modulator (SLM), while the projected interferometric matrix collects up to $O(Q^2)$ image frequencies for a $Q$-core MCF. While this scheme subsumes previous sensing modalities, such as raster scanning (RS) imaging with beamformed illumination, we demonstrate that collecting the measurements of $M$ random SLM configurations--and thus acquiring $M$ SROPs--allows us to estimate an image of interest if $M$ and $Q$ scale log-linearly with the image sparsity level This demonstration is achieved both theoretically, with a specific restricted isometry analysis of the sensing scheme, and with extensive Monte Carlo experiments. On a practical side, we perform a single calibration of the sensing system robust to certain deviations to the theoretical model and independent of the sketching vectors used during the imaging phase. Experimental results made on an actual MCF system demonstrate the effectiveness of this imaging procedure on a benchmark image.