Since the single-pixel imaging technology based on compressive sensing was proposed, single-pixel three-dimension (3D) imaging has attracted a lot of attention in the scientific research circle, because it also has the advantages of wide waveband and high sensitivity. In this paper, the calibration of fringe projection 3D measurement and point cloud computing method are applied to the field of single-pixel 3D imaging. The deformed fringe images are compressed and reconstructed using greedy algorithms and L1 norm minimization method. Finally, the 3D point cloud information of the object is calculated from the deformed image. We designed a simpler imaging system, compared the accuracy differences of different compression ratios and reconstruction algorithms in 3D measurement, and the results of simulation analysis were given at the end of the paper.
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