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

^*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › 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. © 2023 IEEE.

Original language	English
Title of host publication	2023 Opto-Electronics and Communications Conference (OECC)
Publisher	IEEE
Number of pages	3
ISBN (Electronic)	978-1-6654-6213-6
ISBN (Print)	978-1-6654-6214-3
DOIs	https://doi.org/10.1109/OECC56963.2023.10209984
Publication status	Published - 2023
Event	2023 Opto-Electronics and Communications Conference, OECC 2023 - Shanghai, China Duration: 2 Jul 2023 → 6 Jul 2023

Publication series

Name	Opto-Electronics and Communications Conference, OECC
ISSN (Print)	2166-8884
ISSN (Electronic)	2166-8892

Conference

Conference	2023 Opto-Electronics and Communications Conference, OECC 2023
Place	China
City	Shanghai
Period	2/07/23 → 6/07/23

Research Keywords

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

RGC Funding Information

RGC-funded

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10.1109/OECC56963.2023.10209984

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@inproceedings{0eb28b62227a40b3a2df2a8cfad5bc6b,

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. {\textcopyright} 2023 IEEE.",

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",

year = "2023",

doi = "10.1109/OECC56963.2023.10209984",

language = "English",

isbn = "978-1-6654-6214-3",

series = "Opto-Electronics and Communications Conference, OECC",

publisher = "IEEE",

booktitle = "2023 Opto-Electronics and Communications Conference (OECC)",

address = "United States",

note = "2023 Opto-Electronics and Communications Conference, OECC 2023 ; Conference date: 02-07-2023 Through 06-07-2023",

}

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). Opto-Electronics 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

High-Speed Image Edge Detector Based on Thin-Film Lithium Niobate. / Feng, Hanke; Ge, Tong; Guo, Xiaoqing et al.
2023 Opto-Electronics and Communications Conference (OECC). IEEE, 2023. (Opto-Electronics and Communications Conference, OECC).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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

PY - 2023

Y1 - 2023

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. © 2023 IEEE.

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. © 2023 IEEE.

KW - image edge detection

KW - medical diagnosis

KW - microwave photonics

KW - thin-film lithium niobate

UR - https://www.scopus.com/pages/publications/85170210172

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85170210172&origin=recordpage

U2 - 10.1109/OECC56963.2023.10209984

DO - 10.1109/OECC56963.2023.10209984

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 978-1-6654-6214-3

T3 - Opto-Electronics 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

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Research Keywords

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