Spectral Super-Resolution for Multispectral Image Based on Spectral and Spatial Strategies

Chen Yi, Yong Qiang Zhao, Jonathan Cheung Wai Chan

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

1 Scopus citations

Abstract

A spectral super-resolution method is proposed in this paper to recover a high spectral resolution hyperspectral (HS) image from multispectral (MS) images. The proposed method involves spectral improvement strategy and spatial preservation strategy. For spectral improvement strategy, auxiliary MS/HS image pairs of different landscapes are exploited to estimate spectral response relationship so that a HS image is obtained as an intermediate result. Then, spectral dictionary learning is exploited to recover more accurate spectral reconstruction result. Spatial preservation strategy is used as spatial constraint to ensure spatial consistency. Additionally, low rank property of HS image is also introduced to make use of global spectral coherence among HS bands. Experiments are conducted on real MS/HS data (ALI and Hyperion) captured by EO-1 satellite. Experiment results demonstrate the superiority of our proposed method to other state-of-art methods.

Original languageEnglish
Title of host publication2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages851-854
Number of pages4
ISBN (Electronic)9781538691540
DOIs
StatePublished - Jul 2019
Event39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Yokohama, Japan
Duration: 28 Jul 20192 Aug 2019

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
Country/TerritoryJapan
CityYokohama
Period28/07/192/08/19

Keywords

  • Hyperspectral image
  • Low rank
  • Spectral dictionary
  • Spectral resolution enhancement

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