Multichannel Spectral Image Enhancement for Visualizing Diabetic Retinopathy Lesions

Pauli Fält, Masahiro Yamaguchi, Yuri Murakami, Lauri Laaksonen, Lasse Lensu, Ela Claridge, Markku Hauta-kasari, Hannu Uusitalo

Research output: Chapter in Book/Report/Conference proceedingOther chapter contribution

1 Citation (Scopus)
154 Downloads (Pure)


Spectral imaging is a useful tool in many fields of scientific research and industry. Spectral images contain both spatial and spectral information of the scene. Spectral information can be used for effective visualization of the features-of-interest. One approach is to use spectral image enhancement techniques to improve the diagnostic accuracy of medical image technologies like retinal imaging. In this paper, two multichannel spectral image enhancement methods and a technique to further improve the visualization are presented. The methods are tested on four multispectral retinal images which contain diabetic retinopathy lesions. Both of the methods improved the detectability and quantitative contrast of the diabetic lesions when compared to standard color images and are potentially valuable for clinicians and automated image analyses.
Original languageEnglish
Title of host publicationImage and Signal Processing
Subtitle of host publication6th International Conference, ICISP 2014, Cherbourg, France, June 30 – July 2, 2014. Proceedings
EditorsAbderrahim Elmoataz, Olivier Lezoray, Fathallah Nouboud, Driss Mammass
ISBN (Electronic)9783319079981
ISBN (Print)9783319079974
Publication statusPublished - 2014
Event6th International Conference, ICISP 2014 - Cherbourg, France, France
Duration: 30 Jun 20142 Jul 2014

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference6th International Conference, ICISP 2014
CityCherbourg, France,


  • spectral image
  • multispectral imaging
  • principal component analysis
  • enhancement
  • retina
  • diabetes mellitus
  • diabetic retinopathy


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