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

Chan, Antony C. S. and Ng, Ho-Cheung and Bogaraju, Sharat C. V. and So, Hayden K. H. and Lam, Edmund Y. and Tsia, Kevin K. (2017) All-passive pixel super-resolution of time-stretch imaging. Scientific Reports, 7 . Art. No. 44608. ISSN 2045-2322. PMCID PMC5356014. https://resolver.caltech.edu/CaltechAUTHORS:20170417-112751528

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Abstract

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 (≈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.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1038/srep44608DOIArticle
https://www.nature.com/articles/srep44608PublisherArticle
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5356014/PubMed CentralArticle
ORCID:
AuthorORCID
Chan, Antony C. S.0000-0002-5104-261X
So, Hayden K. H.0000-0002-6514-0237
Additional Information:© 2017 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ received: 19 October 2016, accepted: 09 February 2017. Published: 17 March 2017. We thank Queenie T.K. Lai for providing the phytoplankton culture, and Bob C.M. Chung for fabricating the on-chip water-injection and microfluidic inertial flow focusing microscope slides. We also thank Xing Xun for the technical support on unsupervised pattern recognition and classification algorithms. This work is conducted in part using the HKU ITS research computing facilities that are supported in part by the Hong Kong UGC Special Equipment Grant (SEG HKU09). This work is partially supported by grants from the Research Grant Council of the Hong Kong Special Administration Region, China (Project No. 17208414, 717212E, 717911E, 17207715, 17207714, 720112E), Innovation and Technology Support Programme (ITS/090/14), University Development Fund of HKU, and the National Natural Science Foundation of China (NSFC)/Research Grants Council (RGC) Joint Research Scheme (N_HKU714/13). Author Contributions: Conceived and designed the algorithm/experiments: A.C.S.C. Contributed reagents/materials/analysis tools: H.C.N., S.C.V.B., Wrote the paper: A.C.S.C., E.Y.L., K.K.T. Supervised the project: H.K.H.S., E.Y.L., K.K.T. The authors declare no competing financial interests.
Funders:
Funding AgencyGrant Number
Hong Kong University Grants CommitteeSEG HKU09
Research Grants Council of the Hong Kong Special Administrative Region of China17208414
Research Grants Council of the Hong Kong Special Administrative Region of China717212E
Research Grants Council of the Hong Kong Special Administrative Region of China717911E
Research Grants Council of the Hong Kong Special Administrative Region of China17207715
Research Grants Council of the Hong Kong Special Administrative Region of China17207714
Research Grants Council of the Hong Kong Special Administrative Region of China720112E
Research Grants Council of the Hong Kong Special Administrative Region of ChinaITS/090/14
Hong Kong UniversityUNSPECIFIED
National Natural Science Foundation of ChinaN_HKU714/13
PubMed Central ID:PMC5356014
Record Number:CaltechAUTHORS:20170417-112751528
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20170417-112751528
Official Citation:Chan, A. C. S. et al. All-passive pixel super-resolution of time-stretch imaging. Sci. Rep. 7, 44608; doi: 10.1038/srep44608 (2017).
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:76599
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:17 Apr 2017 19:41
Last Modified:03 Oct 2019 17:02

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