All-passive pixel super-resolution of time-stretch imaging

Antony C. S. Chan, Ho Cheung Ng, Sharatchandra Varma Bogaraju, Hayden Kwok Hay So, Edmund Y. Lam, Kevin K. Tsia

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)
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Based on image encoding in a serial-temporal format, optical time-stretch imaging entails a stringent requirement of state-of-the- art fast data acquisition unit in order to preserve high image resolution at an ultrahigh frame rate --- hampering the widespread utilities of such technology. Here, we propose a pixel super-resolution (pixel-SR) technique tailored for time-stretch imaging that preserves pixel resolution at a relaxed sampling rate. It harnesses the subpixel shifts between image frames inherently introduced by asynchronous digital sampling of the continuous time-stretch imaging process. Precise pixel registration is thus accomplished without any active opto-mechanical subpixel-shift control or other additional hardware. Here, we present the experimental pixel-SR image reconstruction pipeline that restores high-resolution time-stretch images of microparticles and biological cells (phytoplankton) at a relaxed sampling rate (approx. 2--5 GSa/s) --- more than four times lower than the originally required readout rate (20 GSa/s) --- is thus effective for high-throughput label-free, morphology-based cellular classification down to single-cell precision. Upon integration with the high-throughput image processing technology, this pixel-SR time- stretch imaging technique represents a cost-effective and practical solution for large scale cell-based phenotypic screening in biomedical diagnosis and machine vision for quality control in manufacturing.
Original languageUndefined/Unknown
Article number44608
JournalScientific Reports
Publication statusPublished - 17 Mar 2017

Bibliographical note

17 pages, 8 figures


  • physics.ins-det
  • physics.optics
  • I.4.1, B.2.4, I.3.3, I.4.6

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