Hyperspectral image processing: A direct image simplification method

Christopher A. Neylan, Tyler Rush, Angel Gutierrez, Stefan A. Robila

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

1 Scopus citations

Abstract

We describe a novel approach to produce color composite images from hyperspectral data using weighted spectra averages. The weighted average is based on a sequence of numbers (weights) selected using pixel value information and interband distance. Separate sequences of weights are generated for each of the three color bands forming the color composite image. Tuning of the weighting parameters and emphasis on different spectral areas allows for emphasis of one or other feature in the image. The produced image is a distinct approach from a regular color composite result, since all the bands provide information to the final result. The algorithm was implemented in high level programming language and provided with a user friendly graphical interface. The current design allows for stand-alone usage or for further modifications into a real time visualization module. Experimental results show that the weighted color composition is an extremely fast visualization tool.

Original languageEnglish
Title of host publicationAlgorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV
DOIs
StatePublished - 17 Jun 2008
EventAlgorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV - Orlando, FL, United States
Duration: 17 Mar 200819 Mar 2008

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6966
ISSN (Print)0277-786X

Other

OtherAlgorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIV
CountryUnited States
CityOrlando, FL
Period17/03/0819/03/08

Keywords

  • Color composite images
  • Efficient data display
  • Feature extraction
  • Hyperspectral images

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