Article

Performance evaluation of dimensionality reduction techniques for multispectral images

  1. Pedro Latorre Carmona1,
  2. Reiner Lenz2,*

Article first published online: 10 OCT 2007

DOI: 10.1002/ima.20107

Issue

International Journal of Imaging Systems and Technology

International Journal of Imaging Systems and Technology

Special Issue: Special Issue on Applied Color Image Processing

Volume 17, Issue 3, pages 202–217, 2007

Additional Information

How to Cite

Carmona, P. L. and Lenz, R. (2007), Performance evaluation of dimensionality reduction techniques for multispectral images. Int. J. Imaging Syst. Technol., 17: 202–217. doi: 10.1002/ima.20107

Author Information

  1. 1

    Depto. Lenguajes y Sistemas Informáticos, Universidad Jaume I, Campus del Riu Sec s/n, 12071, Castellón de la Plana, Spain

  2. 2

    Department of Science and Technology, Linköping University, Campus Norrköping, Norrköping, Sweden

*Department of Science and Technology, Linköping University, Campus Norrköping, Norrköping, Sweden

Publication History

  1. Issue published online: 10 OCT 2007
  2. Article first published online: 10 OCT 2007
  3. Manuscript Accepted: 30 AUG 2007
  4. Manuscript Received: 31 JAN 2007

Funded by

  • Ministry of Education and Science of the Spanish Government through the DATASAT. Grant Number: ESP-2005-00724-C05-C05

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Abstract

We consider several collections of multispectral color signals and describe how linear and nonlinear methods can be used to investigate their internal structure. We use databases consisting of blackbody radiators, approximated and measured daylight spectra, multispectral images of indoor and outdoor scenes under different illumination conditions, and numerically computed color signals. We apply principal components analysis, group-theoretical methods and three manifold learning methods: Laplacian Eigenmaps, ISOMAP, and conformal component analysis. Identification of low-dimensional structures in these databases is important for analysis, model building and compression and we compare the results obtained by applying the algorithms to the different databases. © 2007 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 17, 202–217, 2007

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