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

Aburaed, Nour and Alkhatib, Mohammed Q. and Marshall, Stephen and Zabalza, Jaime and Ahmad, Hussain Al; (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) . IEEE, MYS, pp. 1516-1519. ISBN 9781665427920 (https://doi.org/10.1109/igarss46834.2022.9883578)

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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.

ORCID iDs

Aburaed, Nour ORCID logoORCID: https://orcid.org/0000-0002-5906-0249, Alkhatib, Mohammed Q., Marshall, Stephen ORCID logoORCID: https://orcid.org/0000-0001-7079-5628, Zabalza, Jaime ORCID logoORCID: https://orcid.org/0000-0002-0634-1725 and Ahmad, Hussain Al;
  • Item type:Book Section
    ID code:82822
    Dates:
    Date
    Event
    28 September 2022
    Published
    22 July 2022
    Published Online
    4 April 2022
    Accepted
    Notes:© 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.
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:18 Oct 2022 13:43
    Last modified:11 Nov 2024 15:31
    URI:https://strathprints.strath.ac.uk/id/eprint/82822
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