Unsupervised segmentation for hyperspectral images using mean shift segmentation

Sangwook Lee, Chulhee Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

In this paper, we propose an unsupervised segmentation method for hyperspectral images using mean shift filtering. One major problem of traditional mean shift algorithms is the difficulty of determining kernel bandwidths. We address this problem by using efficient clustering methods. First, PCA (Principal Component Analysis) was applied to hyperspectral images and the first three eigenimages were selected. Then, we applied mean shift filtering to the selected images using a kernel with a small bandwidth. This procedure produced a large number of clusters. In order to merge the homogeneous clusters, we used the Bhattacharyya distance. Experiments showed promising segmentation results without requiring user input.

Original languageEnglish
Title of host publicationSatellite Data Compression, Communications, and Processing VI
DOIs
Publication statusPublished - 2010 Oct 18
EventSatellite Data Compression, Communications, and Processing VI - San Diego, CA, United States
Duration: 2010 Aug 32010 Aug 5

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume7810
ISSN (Print)0277-786X

Other

OtherSatellite Data Compression, Communications, and Processing VI
CountryUnited States
CitySan Diego, CA
Period10/8/310/8/5

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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  • Cite this

    Lee, S., & Lee, C. (2010). Unsupervised segmentation for hyperspectral images using mean shift segmentation. In Satellite Data Compression, Communications, and Processing VI [781011] (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 7810). https://doi.org/10.1117/12.862176