Big data is a hot topic today, not only because the world is awash in digital data, but also the fresh information can be mined from the data. But the big data problem isn’t limited to analytics; it also includes data capture, storage and transmission. Compressive sampling (CS) has attracted considerable attention as a novel data sampling technique and widely applied in diverse fields including wideband spectrum sensing and biomedical imaging in recent years. Compared with traditional electric CS systems, photonic-assisted CS technique utilizes can significantly reduce the sampling rate of the back-end analog-to-digital converter (ADC), highly compress the big data. With these techniques, we demonstrated one-dimensional and 2-dimensional high-speed single-pixel imaging systems are implemented with high frame rates three orders of magnitude faster than conventional single-pixel cameras. To show the utility of our scheme in biomedical applications, an imaging flow cytometer with a throughput of 100,000 cells/s is demonstrated, which has settled the big data problem caused by high-throughput image acquisition.
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All optical big data compression in high-speed imaging flow cytometry
Published: 21 July 2017 by MDPI in The 7th International Multidisciplinary Conference on Optofluidics 2017 session Other emerging and multidisciplinary researches