Computational Ghost Imaging With Bessel Beam for Axial Objects

Abstract

In ghost imaging (GI) techniques, if the illumination patterns used in the reconstruction algorithm do not match that incident on the object's surface, the reconstructed image will be blurred. Here, we propose a computational GI system based on Bessel beams (Bessel-GI). Owing to the diffraction-free property of Bessel beams, Bessel-GI can image objects at different, unknown axial positions. It can also image multiple objects at various axial positions and axially moving objects. Specifically, the depth information of the objects can be reflected in the image size. A change in the object's position will scale the Bessel-GI imaging result, and we provide a theoretical analysis of the scale factor. The experimental results demonstrate the feasibility and utility of Bessel-GI, as well as the accuracy of the scaling factor obtained from the theoretical analysis. Bessel-GI has potential applications in moving object GI and 3D-GI. Additionally, the combination of Bessel-GI with microscopy imaging can be effectively applied to non-axial scanning microscopic GI techniques.