Abstract

Ghost Imaging has been extensively explored for 25 years for a two reasons: the rich physics of second-order photon correlations that enable this imaging scheme and the possibility of implementing new imaging protocols with interesting real-life applications, e.g. imaging in turbulent media, investigation of sensitive samples in low-flux regimes, 3-D plenoptic imaging, and so on. Since the first demonstration of Ghost Imaging, several extended versions of the Traditional Ghost Imaging algorithm have been proposed, such as Correspondence Ghost Imaging, Pseudo-Inverse Ghost Imaging, and normalization techniques that rely on different computational approaches to obtain the image from measured data. So far, a direct comparison of all above-mentioned protocols for the same experimental parameters is still lacking. In this work, we experimentally and numerically implement a number of different methods and systematically compare them in terms of the obtained SNR and computational cost. Furthermore, we investigate their compatibility with Correlation Plenoptic Imaging, a technique strictly connected to Ghost Imaging, that allows refocusing of images, increasing the depth of field (DOF) and making 3D visualization possible. Our results can provide useful guidelines for the choice of a suitable numerical algorithm for in the light of Ghost Imaging applications.

Highlights

  • Ghost Imaging (GI) is a fascinating and widely studied technique exploiting spatial or momentum correlations between two beams of light

  • While Traditional Ghost Imaging (TGI), Correspondence Ghost Imaging (CGI) and related normalizations did not exhibit a direct dependence on the image size in the range we considered, the log-log plots for Pseudo-Inverse Ghost Imaging (PGI) and Denoising Pseudo-Inverse Ghost Imaging (DPGI) reveal a scaling of p0.690 and p1.83, respectively, where p is the number of pixels

  • When analyzing Signal-to-Noise Ratio (SNR) performances, we found that normalized and differential protocols related to Traditional Ghost Imaging (TGI) perform the best, with comparable computation times

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Summary

INTRODUCTION

Ghost Imaging (GI) is a fascinating and widely studied technique exploiting spatial or momentum correlations between two beams of light. In this work we present a comparative study of TGI, CGI and PGI, their combination with normalization variants NGI and DGI, as well as DPGI, which is based on PGI, in terms of SNR and computational cost. For these methods exist different protocols to normalize or denoise the image data, which improve the Signal-to-Noise Ratio (SNR).

Traditional Ghost Imaging
Correlation Plenoptic Imaging
Differential and Normalized Ghost Imaging
Correspondence Ghost Imaging and its normalized versions
Pseudo-Inverse Ghost Imaging
Compatibility with Correlation Plenoptic Imaging
CONCLUSION
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