Formation mechanism of correspondence imaging with thermal light

TL;DR

This paper develops a probability theory to explain the formation mechanism of correspondence imaging with thermal light, revealing how conditional averaging of patterns produces ghost images and analyzing the statistical properties of the recovered signals.

Contribution

It introduces a new probabilistic framework for understanding correspondence imaging with thermal light, supported by simulations and experiments.

Findings

Recovered pixel values follow a Gaussian distribution conditioned on gray levels.

Higher bucket values produce higher quality positive images.

The crosspoint-to-standard-deviation ratio quantifies image quality.

Abstract

Correspondence imaging can achieve positive-negative ghost images by just conditional averaging of partial patterns, without treating bucket intensities as weights. To explain its imaging mechanism, we develop a probability theory assuming the targets are of gray-scale and the thermal reference speckles obey an arbitrary independent and identical distribution. By both simulation and experiments, we find that the recovered values in each region of the same original gray value conditionally obey a Gaussian distribution. A crosspoint-to-standard-deviation ratio is used as the figure of merit to prove that the patterns with respect to larger bucket values generate a positive image with a higher quality, vice versa for negative one. This work complements the theory of ghost imaging.