Model-based illumination correction in retinal images

E. Grisan, A. Giani, E. Ceseracciu, A. Ruggeri

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

35 Citations (Scopus)

Abstract

Retinal images are routinely acquired and assessed to provide diagnostic evidence for many important diseases. Because of the acquisition process, very often these images are non-uniformly illuminated and exhibit local luminosity and contrast variability. This problem may seriously affect the diagnostic process and its outcome, especially if an automatic computer-based procedure is used. We propose here a new method to estimate and correct luminosity variation in retinal images. The method uses the hue, saturation, value (HSV) colour space to better decouple the luminance and chromatic information. Then, it fits an illumination model on a proper subregion (the retinal background) of the saturation and value channels. This solves many of the drawbacks of previously proposed methods, as filter-based correction which fails when large lesions or retinal features are present.

Original languageEnglish
Title of host publication2006 3rd IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro - Proceedings
Pages984-987
Number of pages4
DOIs
Publication statusPublished - 8 May 2006
Externally publishedYes
Event2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Arlington, VA, United States
Duration: 6 Apr 20069 Apr 2006

Publication series

Name2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings
Volume2006

Conference

Conference2006 3rd IEEE International Symposium on Biomedical Imaging: From Nano to Macro
Country/TerritoryUnited States
CityArlington, VA
Period6/04/069/04/06

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