An Efficient Method for the Visualization of Spectral Images Based on a Perception-Oriented Spectrum Segmentation

  • Steven Le Moan
  • Alamin Mansouri
  • Yvon Voisin
  • Jon Y. Hardeberg
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6453)


We propose a new method for the visualization of spectral images. It involves a perception-based spectrum segmentation using an adaptable thresholding of the stretched CIE standard observer color-matching functions. This allows for an underlying removal of irrelevant channels, and, consequently, an alleviation of the computational burden of further processings. Principal Components Analysis is then used in each of the three segments to extract the Red, Green and Blue primaries for final visualization. A comparison framework using two different datasets shows the efficiency of the proposed method.


Independent Component Analysis Spectral Image Hyperspectral Image Independent Component Analysis Multispectral Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Steven Le Moan
    • 1
    • 2
  • Alamin Mansouri
    • 1
  • Yvon Voisin
    • 1
  • Jon Y. Hardeberg
    • 2
  1. 1.Le2iUniversité de BourgogneAuxerreFrance
  2. 2.ColorlabHøgskolen i GjøvikNorway

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