SISR of hyperspectral remote sensing imagery using 3D encoder-decoder RUNet architecture

Nour Aburaed; Mohammed Q. Alkhatib; Stephen Marshall; Jaime Zabalza; Hussain Al Ahmad

doi:10.1109/igarss46834.2022.9883578

SISR of hyperspectral remote sensing imagery using 3D encoder-decoder RUNet architecture

Nour Aburaed, Mohammed Q. Alkhatib, Stephen Marshall, Jaime Zabalza, Hussain Al Ahmad

Electronic And Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

2 Citations (Scopus)

7 Downloads (Pure)

Abstract

Single Image Super Resolution (SISR) refers to the spatial enhancement of an image from a single Low Resolution (LR) observation. This topic is of particular interest to remote sensing community, especially in the area of Hyperspectral Imagery (HSI) due to their high spectral resolution but limited spatial resolution. Enhancing the spatial resolution of HSI is a pre-requisite that boosts the accuracy of other image processing tasks, such as object detection and classification. This paper deals with SISR of HSI through the 3D expansion of Robust UNet (RUNet). The network is developed, trained, and tested over two datasets, and compared against the original 2D-RUNet and other state-of-the-art approaches. Quantitative and qualitative evaluation show the superiority of 3D-RUNet and its ability to preserve the spectral fidelity of the enhanced HSI.

Original language	English
Title of host publication	IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	1516-1519
Number of pages	4
ISBN (Electronic)	9781665427920
ISBN (Print)	9781665427920
DOIs	https://doi.org/10.1109/igarss46834.2022.9883578
Publication status	Published - 28 Sep 2022
Event	2022 IEEE International Geoscience and Remote Sensing Symposium - Kuala Lumpur Convention Centre (KLCC), Kuala Lumpur, Malaysia Duration: 17 Jul 2022 → 22 Jul 2022 https://www.igarss2022.org/

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)
Volume	2022-July

Conference

Conference	2022 IEEE International Geoscience and Remote Sensing Symposium
Abbreviated title	IGARSS
Country/Territory	Malaysia
City	Kuala Lumpur
Period	17/07/22 → 22/07/22
Internet address	https://www.igarss2022.org/

Keywords

hyperspectral
remote sensing
single image super resolution
3D convolution
3D-RUNet

Access to Document

10.1109/igarss46834.2022.9883578

Aburaed-etal-IGARSS-2022-SISR-of-hyperspectral-remote-sensing-imagery-using-3D-encoder-decoderAccepted author manuscript, 813 KBLicence: Strath_1

Cite this

Aburaed, N., Alkhatib, M. Q., Marshall, S., Zabalza, J., & Ahmad, H. A. (2022). SISR of hyperspectral remote sensing imagery using 3D encoder-decoder RUNet architecture. In IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium (pp. 1516-1519). (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2022-July). IEEE. https://doi.org/10.1109/igarss46834.2022.9883578

@inproceedings{087362e3037842959ea46dda0879ef1c,

title = "SISR of hyperspectral remote sensing imagery using 3D encoder-decoder RUNet architecture",

abstract = "Single Image Super Resolution (SISR) refers to the spatial enhancement of an image from a single Low Resolution (LR) observation. This topic is of particular interest to remote sensing community, especially in the area of Hyperspectral Imagery (HSI) due to their high spectral resolution but limited spatial resolution. Enhancing the spatial resolution of HSI is a pre-requisite that boosts the accuracy of other image processing tasks, such as object detection and classification. This paper deals with SISR of HSI through the 3D expansion of Robust UNet (RUNet). The network is developed, trained, and tested over two datasets, and compared against the original 2D-RUNet and other state-of-the-art approaches. Quantitative and qualitative evaluation show the superiority of 3D-RUNet and its ability to preserve the spectral fidelity of the enhanced HSI.",

keywords = "hyperspectral, remote sensing, single image super resolution, 3D convolution, 3D-RUNet",

author = "Nour Aburaed and Alkhatib, {Mohammed Q.} and Stephen Marshall and Jaime Zabalza and Ahmad, {Hussain Al}",

note = "{\textcopyright} 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.; 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS ; Conference date: 17-07-2022 Through 22-07-2022",

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month = sep,

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doi = "10.1109/igarss46834.2022.9883578",

language = "English",

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series = "International Geoscience and Remote Sensing Symposium (IGARSS)",

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Aburaed, N, Alkhatib, MQ, Marshall, S , Zabalza, J & Ahmad, HA 2022, SISR of hyperspectral remote sensing imagery using 3D encoder-decoder RUNet architecture. in IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. International Geoscience and Remote Sensing Symposium (IGARSS), vol. 2022-July, IEEE, Piscataway, NJ, pp. 1516-1519, 2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, Malaysia, 17/07/22. https://doi.org/10.1109/igarss46834.2022.9883578

SISR of hyperspectral remote sensing imagery using 3D encoder-decoder RUNet architecture. / Aburaed, Nour; Alkhatib, Mohammed Q.; Marshall, Stephen et al.

IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. Piscataway, NJ : IEEE, 2022. p. 1516-1519 (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2022-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book

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AU - Aburaed, Nour

AU - Alkhatib, Mohammed Q.

AU - Marshall, Stephen

AU - Zabalza, Jaime

AU - Ahmad, Hussain Al

N1 - © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

PY - 2022/9/28

Y1 - 2022/9/28

N2 - Single Image Super Resolution (SISR) refers to the spatial enhancement of an image from a single Low Resolution (LR) observation. This topic is of particular interest to remote sensing community, especially in the area of Hyperspectral Imagery (HSI) due to their high spectral resolution but limited spatial resolution. Enhancing the spatial resolution of HSI is a pre-requisite that boosts the accuracy of other image processing tasks, such as object detection and classification. This paper deals with SISR of HSI through the 3D expansion of Robust UNet (RUNet). The network is developed, trained, and tested over two datasets, and compared against the original 2D-RUNet and other state-of-the-art approaches. Quantitative and qualitative evaluation show the superiority of 3D-RUNet and its ability to preserve the spectral fidelity of the enhanced HSI.

AB - Single Image Super Resolution (SISR) refers to the spatial enhancement of an image from a single Low Resolution (LR) observation. This topic is of particular interest to remote sensing community, especially in the area of Hyperspectral Imagery (HSI) due to their high spectral resolution but limited spatial resolution. Enhancing the spatial resolution of HSI is a pre-requisite that boosts the accuracy of other image processing tasks, such as object detection and classification. This paper deals with SISR of HSI through the 3D expansion of Robust UNet (RUNet). The network is developed, trained, and tested over two datasets, and compared against the original 2D-RUNet and other state-of-the-art approaches. Quantitative and qualitative evaluation show the superiority of 3D-RUNet and its ability to preserve the spectral fidelity of the enhanced HSI.

KW - hyperspectral

KW - remote sensing

KW - single image super resolution

KW - 3D convolution

KW - 3D-RUNet

U2 - 10.1109/igarss46834.2022.9883578

DO - 10.1109/igarss46834.2022.9883578

M3 - Conference contribution book

SN - 9781665427920

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

SP - 1516

EP - 1519

BT - IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium

PB - IEEE

CY - Piscataway, NJ

T2 - 2022 IEEE International Geoscience and Remote Sensing Symposium

Y2 - 17 July 2022 through 22 July 2022

ER -

Aburaed N, Alkhatib MQ, Marshall S , Zabalza J, Ahmad HA. SISR of hyperspectral remote sensing imagery using 3D encoder-decoder RUNet architecture. In IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. Piscataway, NJ: IEEE. 2022. p. 1516-1519. (International Geoscience and Remote Sensing Symposium (IGARSS)). Epub 2022 Jul 22. doi: 10.1109/igarss46834.2022.9883578

SISR of hyperspectral remote sensing imagery using 3D encoder-decoder RUNet architecture

Abstract

Publication series

Conference

Keywords

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