Abstract
In this paper, we propose a compression sensing ghost imaging algorithm to reduce the computation time with high image quality via compression sensing based on the total variation reconstruction. A small amount of measurements can be used for shortening the sampling time. The total variation is used as criteria during the search process. It makes the ghost image achieving a high image reconstruction quality. The simulation results demonstrate that the proposed method can enhance imaging quality with the reduced computation time.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (Grant Nos. 61572529, 61871407, 61872390, 61801522), and the Natural Science Foundation of the Jiangsu Higher Education Institutions of China (Grant No. 18KJB510045).
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Zhu, R., Li, G. & Guo, Y. Compressed-Sensing-based Gradient Reconstruction for Ghost Imaging. Int J Theor Phys 58, 1215–1226 (2019). https://doi.org/10.1007/s10773-019-04013-x
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DOI: https://doi.org/10.1007/s10773-019-04013-x