Moving Object Captured with Pink Noise Pattern in Computational Ghost Imaging

TL;DR

This paper introduces a pink noise pattern-based computational ghost imaging method that effectively captures moving objects, outperforming traditional white noise approaches by requiring fewer patterns and achieving higher SNR.

Contribution

The authors develop and experimentally validate a pink noise pattern technique in CGI that improves imaging of moving objects, especially when white noise methods fail.

Findings

Successfully images oscillating objects with pink noise in CGI.

Outperforms white noise in terms of pattern efficiency and SNR.

Enables imaging of moving objects where traditional methods fail.

Abstract

We develop and experimentally demonstrate an imaging method based on the pink noise pattern in the computational ghost imaging (CGI) system, which has a strong ability to photograph moving objects. To examine its unique ability and scope of application, the object oscillates with variable amplitude in horizontal axis, and the result via commonly used white noise are also measured as a comparison. We show that our method can image the object when the white noise method fails. In addition, our method uses less number of patterns, and enhances the signal-to-noise ratio (SNR) to a great extent.