Unsupervised Spatial-Spectral Hyperspectral Image Reconstruction and Clustering with Diffusion Geometry

Kangning CUI, Ruoning LI, Sam L. POLK, James M. MURPHY, Robert J. PLEMMONS, Raymond H. CHAN*

*Corresponding author for this work

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

2 Citations (Scopus)

Abstract

Hyperspectral images, which store a hundred or more spectral bands of reflectance, have become an important data source in natural and social sciences. Hyperspectral images are often generated in large quantities at a relatively coarse spatial resolution. As such, unsupervised machine learning algorithms incorporating known structure in hyperspectral imagery are needed to analyze these images automatically. This work introduces the Spatial-Spectral Image Reconstruction and Clustering with Diffusion Geometry (DSIRC) algorithm for partitioning highly mixed hyperspectral images. DSIRC reduces measurement noise through a shape-adaptive reconstruction procedure. In particular, for each pixel, DSIRC locates spectrally correlated pixels within a data-adaptive spatial neighborhood and reconstructs that pixel's spectral signature using those of its neighbors. DSIRC then locates high-density, high-purity pixels far in diffusion distance (a data-dependent distance metric) from other high-density, high-purity pixels and treats these as cluster exemplars, giving each a unique label. Non-modal pixels are assigned the label of their diffusion distance-nearest neighbor of higher density and purity that is already labeled. Strong numerical results indicate that incorporating spatial information through image reconstruction substantially improves the performance of pixel-wise clustering.

Original languageEnglish
Title of host publication2022 12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS 2022
PublisherIEEE
Number of pages5
ISBN (Electronic)9781665470698
DOIs
Publication statusPublished - 2022
Externally publishedYes
Event12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS 2022 - Rome, Italy
Duration: 13 Sept 202216 Sept 2022

Publication series

NameWorkshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensing
Volume2022-September
ISSN (Print)2158-6276

Conference

Conference12th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, WHISPERS 2022
Country/TerritoryItaly
CityRome
Period13/09/2216/09/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Funding

This work was supported in part by HKRGC Grants No. CUHK14301718, CityU11301120, C1013-21GF, CityU Grant 9380101.

Keywords

  • Clustering
  • Diffusion Geometry
  • Hyperspectral Imagery
  • Image Reconstruction
  • Spectral Unmixing
  • Unsupervised Learning

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