Year: 2025
Type: article
Abstract: 3-D single-pixel imaging (SPI) is a promising imaging technique that can be flexibly applied to various wavebands. The main challenge in 3-D SPI is that the calibration usually requires a large number of standard points as references, which are tricky to capture using single-pixel detectors (SPDs). 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 efficiently generate the standard points from one single image. The technique of deep learning and digital twin guarantees the CaliF’s high accuracy. We conduct experiments with our new method to verify its validity and accuracy, implying it holds great potential in 3-D SPI systems or other general imaging systems.
Authors: Xinyue Ma, Chenxing Wang
Institution: Southeast University
Language: English
Subfield: Acoustics and Ultrasonics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
Award: G3104959772
OpenAlex ID: W4408858456