Hyperspectral image destriping using unmixing-based kriging interpolation

Cencen Pan, Kun Tan, Qian Du, Qinwu Yan, Jianwei Ding

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

3 Scopus citations

Abstract

Stripes in hyperspectral imagery reduce image quality and limit further applications. In this paper, we propose a novel destriping method. In this method, reference spectra is extracted in VNIR bands and linear unmixing is performed to denoise these bands, and abundance maps derived by VNIR bands are then used to repair SWIR bands. The error term of all the SWIR bands is also calculated, and the kriging interpolation method is used to interpolate error term, deriving the final destriped SWIR images. Destriping results shown that the proposed method outperforms the traditional kriging interpolation with visual inspection and quantitative assessment.

Original languageEnglish
Title of host publication2016 8th Workshop on Hyperspectral Image and Signal Processing
Subtitle of host publicationEvolution in Remote Sensing, WHISPERS 2016
PublisherIEEE Computer Society
ISBN (Electronic)9781509006083
DOIs
StatePublished - 28 Jun 2016
Externally publishedYes
Event8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2016 - Los Angeles, United States
Duration: 21 Aug 201624 Aug 2016

Publication series

NameWorkshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
Volume0
ISSN (Print)2158-6276

Conference

Conference8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS 2016
Country/TerritoryUnited States
CityLos Angeles
Period21/08/1624/08/16

Keywords

  • Destriping
  • Hyperspectral imagery
  • Kriging interpolation
  • Unmixing

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