HYPERSPECTRAL AND MULTISPECTRAL IMAGE FUSION: FROM MODEL-DRIVEN TO DATA-DRIVEN

Yongqiang Zhao, Haofang Yan, Sha Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Hyperspectral image (HSI) provides rich spectral information, which has been used in object detection, environmental protection. However, HSI suffers from low spatial resolution owing to the limitations of imaging systems. Hyperspectral and multispectral image (MSI) fusion is an efficient way to enhance the spatial resolution of HSI. In past decades, many HSI and MSI fusion algorithms have been presented in the literature. In this paper, we present a comprehensive review for the HSI-MSI fusion methods. According to the characteristics and trend of HSI-MSI fusion methods, they are categorized as two classes: model-driven approaches and data-driven approaches. We clarify their characteristics, advantages and also make a comparison and discussion for the fusion methods in each category. Additionally, we analyze the existing challenges and present the potential research directions for HSI-MSI fusion method.

Original languageEnglish
Title of host publicationIGARSS 2021 - 2021 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1256-1259
Number of pages4
ISBN (Electronic)9781665403696
DOIs
StatePublished - 2021
Event2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 - Brussels, Belgium
Duration: 12 Jul 202116 Jul 2021

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2021-July

Conference

Conference2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021
Country/TerritoryBelgium
CityBrussels
Period12/07/2116/07/21

Keywords

  • Data-driven
  • Hyperspectral and multispectral image fusion
  • Model-driven

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