Ghost imaging for an occluded object

TL;DR

This paper presents a computational ghost imaging method capable of reconstructing images of objects behind obstacles, with analysis on how distance, wavelength, and detector placement affect image quality, supported by simulations.

Contribution

It introduces a novel ghost imaging scheme for occluded objects, analyzing key factors influencing image reconstruction and demonstrating robustness through simulations.

Findings

Image quality improves with increased object-obstacle distance.

Wavelength of light source impacts the reconstructed image quality.

A simple point detector can be used if placed far from the obstacle.

Abstract

Imaging for an occluded object is usually a difficult problem, in this letter, we introduce an imaging scheme based on computational ghost imaging, which can obtain the image of a target object behind an obstacle. According to our theoretical analysis, once the distance between the object and the obstacle is far enough, one can obtain the image of the object by using ghost imaging technique. The wavelength of the light source also affects the quality of the reconstructed image. In addition, if the bucket detector is placed far away from the obstacle, a tiny point-like detector without collecting lens can be applied to realize the imaging. These theoretical results above have been verified with our numerical simulations. Furthermore, the robustness of this imaging scheme is also investigated.