Calibration of 3D Single-pixel Imaging Systems with a Calibration Field
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 12 of its 60 references that are in the map. First posted on arXiv 10 Oct 2024.
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12 of 60 references.
References · 12
- 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
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- 2018Deep ChArUco: Dark ChArUco Marker Pose Estimationcited by 18
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- 2022Portrait Eyeglasses and Shadow Removal by Leveraging 3D Synthetic Datacited by 11
- 2021Single-shot fringe projection profilometry based on Deep Learning and Computer Graphicscited by 5
- 2019Ultra-high-speed color imaging with single-pixel detectors under low light levelcited by 3
- 20213D Fourier ghost imaging via semi-calibrated photometric stereocited by 2
- 2019Phase-sensitive x-ray ghost imagingcited by 1
- 20223D Single-pixel imaging with active sampling patterns and learning based reconstructioncited by 1
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