Nonlocal imaging by conditional averaging of random reference measurements

TL;DR

This paper demonstrates a nonlocal imaging technique using conditional averaging of random reference measurements, eliminating the need for correlation calculations and improving efficiency and visibility over traditional ghost imaging methods.

Contribution

It introduces a novel correspondence imaging method that simplifies nonlocal imaging by avoiding correlation calculations, reducing data and computation requirements.

Findings

Reduces number of exposures needed for imaging

Improves image visibility compared to traditional methods

Eliminates correlation calculations in the imaging process

Abstract

We report the nonlocal imaging of an object by conditional averaging of the random exposure frames of a reference detector, which only sees the freely propagating field from a thermal light source. A bucket detector, synchronized with the reference detector, records the intensity fluctuations of an identical beam passing through the object mask. These fluctuations are sorted according to their values relative to the mean, then the reference data in the corresponding time-bins for a given fluctuation range are averaged, to produce either positive or negative images. Since no correlation calculations are involved, this correspondence imaging technique challenges our former interpretations of "ghost" imaging. Compared with conventional correlation imaging or compressed sensing schemes, both the number of exposures and computation time are greatly reduced, while the visibility is much improved. A simple statistical model is presented to explain the phenomenon.