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dc.contributor.authorKang, Ji-Hoon-
dc.contributor.authorKim, Minjeong-
dc.contributor.authorAhn, Jongtae-
dc.contributor.authorHwang, Do Kyung-
dc.contributor.authorPark, Jinwoo-
dc.contributor.authorJu, Byeong-Kwon-
dc.contributor.authorKim, Myungha-
dc.contributor.authorPark, Min-Chul-
dc.date.accessioned2024-01-19T10:37:32Z-
dc.date.available2024-01-19T10:37:32Z-
dc.date.created2022-03-07-
dc.date.issued2019-
dc.identifier.issn0277-786X-
dc.identifier.urihttps://pubs.kist.re.kr/handle/201004/114317-
dc.description.abstractThe properties of photoelectrochemical (PEC) cells have mainly been investigated with a focus on PEC hydrogen production. Because anodic current begins to flow when PEC cell is under illumination, and that this current varies as a function of light intensity, PEC cells can be used as a photodetector. Different from other image sensors, PEC cells can detect the light immersed in solutions due to their PEC properties. To verify the feasibility of using silicon-based PEC cell as an image sensor, we demonstrated a single pixel imaging system based on compressive sensing. Compressive sensing is an algorithm designed to recover signals from a small number of measurements, assuming that the signal of interest can be represented in a sparse way. In this study, we have demonstrated multispectral imaging using a silicon-based PEC cell with compressive sensing. The images were obtained in three primary colors (red, green, and blue). Due to the high photoresponse, stability and unique characteristic that silicon-based PEC cell can be used underwater, the silicon-based PEC cell is expected to be utilized in the future as a photodetector for various applications. We believe this study would be a great example of advanced developments in an optoelectronic system based on PEC cells.-
dc.languageEnglish-
dc.publisherSPIE-INT SOC OPTICAL ENGINEERING-
dc.titleMultispectral compressive sensing using a silicon-based PEC cell-
dc.typeConference-
dc.identifier.doi10.1117/12.2521417-
dc.description.journalClass1-
dc.identifier.bibliographicCitationConference on Computational Imaging IV, v.10990-
dc.citation.titleConference on Computational Imaging IV-
dc.citation.volume10990-
dc.citation.conferencePlaceUS-
dc.citation.conferencePlaceBaltimore, MD-
dc.citation.conferenceDate2019-04-14-
dc.relation.isPartOfCOMPUTATIONAL IMAGING IV-
dc.identifier.wosid000502026100010-
dc.identifier.scopusid2-s2.0-85072638657-
dc.type.docTypeProceedings Paper-
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KIST Conference Paper > 2019
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