Calibration of 3D Single-pixel Imaging Systems with a Calibration Field

TL;DR

This paper introduces a novel calibration method for 3D single-pixel imaging systems using a Calibration Field generated from a single image, leveraging deep learning and digital twin techniques for high accuracy.

Contribution

The work presents a new calibration approach that reduces complexity and data requirements by using a Calibration Field and advanced techniques, improving efficiency in 3D SPI calibration.

Findings

High accuracy calibration achieved with a single image

Reduction in calibration images needed compared to traditional methods

Potential application to various imaging systems

Abstract

3D single-pixel imaging (SPI) is a promising imaging technique that can be ffexibly applied to various wavebands. The main challenge in 3D SPI is that the calibration usually requires a large number of standard points as references, which are tricky to capture using single-pixel detectors. Conventional solutions involve sophisticated device deployment and cumbersome operations, resulting in hundreds of images needed for calibration. In our work, we construct a Calibration Field (CaliF) to efffciently generate the standard points from one single image. A high accuracy of the CaliF is guaranteed by the technique of deep learning and digital twin. We perform experiments with our new method to verify its validity and accuracy. We believe our work holds great potential in 3D SPI systems or even general imaging systems.