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Super Resolution Hyperspectral Imaging based Automated Inspection of Nuclear Fuel Pellets

Research output: Contribution to conference - Without ISBN/ISSN › Abstract › peer-review

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Super Resolution Hyperspectral Imaging based Automated Inspection of Nuclear Fuel Pellets. / Zabalza, Jaime; Parker, Andrew; Bandala Sanchez, Manuel et al.
2022. Abstract from 2022 IEEE Nuclear Science Symposium, Milan, Italy.

Research output: Contribution to conference - Without ISBN/ISSN › Abstract › peer-review

Harvard

Zabalza, J, Parker, A, Bandala Sanchez, M, Murray, P, Marshall, S, Ma, X, Taylor, CJ & Joyce, M 2022, 'Super Resolution Hyperspectral Imaging based Automated Inspection of Nuclear Fuel Pellets', 2022 IEEE Nuclear Science Symposium, Milan, Italy, 5/11/22 - 12/11/22.

APA

Zabalza, J., Parker, A., Bandala Sanchez, M., Murray, P., Marshall, S., Ma, X., Taylor, C. J., & Joyce, M. (2022). Super Resolution Hyperspectral Imaging based Automated Inspection of Nuclear Fuel Pellets. Abstract from 2022 IEEE Nuclear Science Symposium, Milan, Italy.

Vancouver

Zabalza J, Parker A, Bandala Sanchez M, Murray P, Marshall S, Ma X et al.. Super Resolution Hyperspectral Imaging based Automated Inspection of Nuclear Fuel Pellets. 2022. Abstract from 2022 IEEE Nuclear Science Symposium, Milan, Italy.

Author

Zabalza, Jaime ; Parker, Andrew ; Bandala Sanchez, Manuel et al. / Super Resolution Hyperspectral Imaging based Automated Inspection of Nuclear Fuel Pellets. Abstract from 2022 IEEE Nuclear Science Symposium, Milan, Italy.2 p.

Bibtex

@conference{54a8daafbafc423bbf1a3e344066b933,
title = "Super Resolution Hyperspectral Imaging based Automated Inspection of Nuclear Fuel Pellets",
abstract = "This work presents a new methodology for the automated inspection of nuclear fuel pellets based on Single Image Super Resolution (SISR) and Hyperspectral Imaging (HSI). HSI technology provides optical images in which the pixels contain comprehensive spectral information, normally hundreds of channels (wavelengths) covering the Visible Near InfraRed (VNIR) region in the electromagnetic spectrum. Therefore, the spectral information provided by HSI can be used for inspecting images of pellets pixel-wise. However, the spatial resolution in HSI is lower in comparison to conventional imaging, and SISR is proposed for enhancing the HSI images. Results showed how techniques such as Principal Component Analysis (PCA) can be applied to SR-HSI images to effectively exploit the HSI spatialspectral content and generate maps for the automated detection of potential abnormalities on the surface of nuclear fuel pellets. While experiments used color chalk as analogues of PWR pellets, results with sintered UO2 will be presented at the conference. ",
author = "Jaime Zabalza and Andrew Parker and {Bandala Sanchez}, Manuel and Paul Murray and Stephen Marshall and Xiandong Ma and Taylor, {C. James} and Malcolm Joyce",
year = "2022",
month = nov,
day = "7",
language = "English",
note = "2022 IEEE Nuclear Science Symposium ; Conference date: 05-11-2022 Through 12-11-2022",

}

RIS

TY - CONF

T1 - Super Resolution Hyperspectral Imaging based Automated Inspection of Nuclear Fuel Pellets

AU - Zabalza, Jaime

AU - Parker, Andrew

AU - Bandala Sanchez, Manuel

AU - Murray, Paul

AU - Marshall, Stephen

AU - Ma, Xiandong

AU - Taylor, C. James

AU - Joyce, Malcolm

PY - 2022/11/7

Y1 - 2022/11/7

N2 - This work presents a new methodology for the automated inspection of nuclear fuel pellets based on Single Image Super Resolution (SISR) and Hyperspectral Imaging (HSI). HSI technology provides optical images in which the pixels contain comprehensive spectral information, normally hundreds of channels (wavelengths) covering the Visible Near InfraRed (VNIR) region in the electromagnetic spectrum. Therefore, the spectral information provided by HSI can be used for inspecting images of pellets pixel-wise. However, the spatial resolution in HSI is lower in comparison to conventional imaging, and SISR is proposed for enhancing the HSI images. Results showed how techniques such as Principal Component Analysis (PCA) can be applied to SR-HSI images to effectively exploit the HSI spatialspectral content and generate maps for the automated detection of potential abnormalities on the surface of nuclear fuel pellets. While experiments used color chalk as analogues of PWR pellets, results with sintered UO2 will be presented at the conference.

AB - This work presents a new methodology for the automated inspection of nuclear fuel pellets based on Single Image Super Resolution (SISR) and Hyperspectral Imaging (HSI). HSI technology provides optical images in which the pixels contain comprehensive spectral information, normally hundreds of channels (wavelengths) covering the Visible Near InfraRed (VNIR) region in the electromagnetic spectrum. Therefore, the spectral information provided by HSI can be used for inspecting images of pellets pixel-wise. However, the spatial resolution in HSI is lower in comparison to conventional imaging, and SISR is proposed for enhancing the HSI images. Results showed how techniques such as Principal Component Analysis (PCA) can be applied to SR-HSI images to effectively exploit the HSI spatialspectral content and generate maps for the automated detection of potential abnormalities on the surface of nuclear fuel pellets. While experiments used color chalk as analogues of PWR pellets, results with sintered UO2 will be presented at the conference.

M3 - Abstract

T2 - 2022 IEEE Nuclear Science Symposium

Y2 - 5 November 2022 through 12 November 2022

ER -