High-Speed Image Edge Detector Based on Thin-Film Lithium Niobate

Hanke Feng; Tong Ge; Xiaoqing Guo; Yixuan Yuan; Cheng Wang

doi:10.1109/OECC56963.2023.10209984

High-Speed Image Edge Detector Based on Thin-Film Lithium Niobate

Hanke Feng, Tong Ge, Xiaoqing Guo, Yixuan Yuan, Cheng Wang

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

Abstract

We report a high-speed image edge detector based on an integrated lithium niobate photonic chip with processing sampling rates up to 92 GSa/s. We further use the devices to realize photonics-assisted segmentation of medical images.

Original language	English
Title of host publication	2023 Opto-Electronics and Communications Conference (OECC)
Publisher	IEEE
Number of pages	3
ISBN (Electronic)	9781665462136
DOIs	https://doi.org/10.1109/OECC56963.2023.10209984
Publication status	Published - 2 Jul 2023
Event	2023 Opto-Electronics and Communications Conference, OECC 2023 - Shanghai, China Duration: 2 Jul 2023 → 6 Jul 2023 https://ieeexplore.ieee.org/xpl/conhome/10209604/proceeding

Publication series

Name	OptoElectronics and Communications Conference, OECC

Conference

Conference	2023 Opto-Electronics and Communications Conference, OECC 2023
Country/Territory	China
City	Shanghai
Period	2/07/23 → 6/07/23
Internet address	https://ieeexplore.ieee.org/xpl/conhome/10209604/proceeding

Scopus Subject Areas

Computer Networks and Communications
Electrical and Electronic Engineering
Atomic and Molecular Physics, and Optics

User-Defined Keywords

image edge detection
medical diagnosis
microwave photonics
thin-film lithium niobate

Access to Document

10.1109/OECC56963.2023.10209984

Cite this

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title = "High-Speed Image Edge Detector Based on Thin-Film Lithium Niobate",

abstract = "We report a high-speed image edge detector based on an integrated lithium niobate photonic chip with processing sampling rates up to 92 GSa/s. We further use the devices to realize photonics-assisted segmentation of medical images.",

keywords = "image edge detection, medical diagnosis, microwave photonics, thin-film lithium niobate",

author = "Hanke Feng and Tong Ge and Xiaoqing Guo and Yixuan Yuan and Cheng Wang",

note = "We thank the funding of National Natural Science Foundation of China (61922092); Research Grants Council, University Grants Committee (CityU 11204820, CityU 21208219, N_CityU113/20); Croucher Foundation (9509005); City University of Hong Kong (9610402, 9610455). Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 Opto-Electronics and Communications Conference, OECC 2023 ; Conference date: 02-07-2023 Through 06-07-2023",

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doi = "10.1109/OECC56963.2023.10209984",

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series = "OptoElectronics and Communications Conference, OECC",

publisher = "IEEE",

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address = "United States",

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}

Feng, H, Ge, T, Guo, X, Yuan, Y & Wang, C 2023, High-Speed Image Edge Detector Based on Thin-Film Lithium Niobate. in 2023 Opto-Electronics and Communications Conference (OECC). OptoElectronics and Communications Conference, OECC, IEEE, 2023 Opto-Electronics and Communications Conference, OECC 2023, Shanghai, China, 2/07/23. https://doi.org/10.1109/OECC56963.2023.10209984

TY - GEN

T1 - High-Speed Image Edge Detector Based on Thin-Film Lithium Niobate

AU - Feng, Hanke

AU - Ge, Tong

AU - Guo, Xiaoqing

AU - Yuan, Yixuan

AU - Wang, Cheng

N1 - We thank the funding of National Natural Science Foundation of China (61922092); Research Grants Council, University Grants Committee (CityU 11204820, CityU 21208219, N_CityU113/20); Croucher Foundation (9509005); City University of Hong Kong (9610402, 9610455). Publisher Copyright: © 2023 IEEE.

PY - 2023/7/2

Y1 - 2023/7/2

N2 - We report a high-speed image edge detector based on an integrated lithium niobate photonic chip with processing sampling rates up to 92 GSa/s. We further use the devices to realize photonics-assisted segmentation of medical images.

AB - We report a high-speed image edge detector based on an integrated lithium niobate photonic chip with processing sampling rates up to 92 GSa/s. We further use the devices to realize photonics-assisted segmentation of medical images.

KW - image edge detection

KW - medical diagnosis

KW - microwave photonics

KW - thin-film lithium niobate

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U2 - 10.1109/OECC56963.2023.10209984

DO - 10.1109/OECC56963.2023.10209984

M3 - Conference proceeding

AN - SCOPUS:85170210172

T3 - OptoElectronics and Communications Conference, OECC

BT - 2023 Opto-Electronics and Communications Conference (OECC)

PB - IEEE

T2 - 2023 Opto-Electronics and Communications Conference, OECC 2023

Y2 - 2 July 2023 through 6 July 2023

ER -

High-Speed Image Edge Detector Based on Thin-Film Lithium Niobate

Abstract

Publication series

Conference

Scopus Subject Areas

User-Defined Keywords

Access to Document

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