Luminosity and contrast normalization in retinal images.

Retinal images are routinely acquired and assessed to provide diagnostic evidence for many important diseases, e.g. diabetes or hypertension. 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 to derive diagnostic parameters. We propose here a new method to normalize luminosity and contrast in retinal images, both intra- and inter-image. The method is based on the estimation of the luminosity and contrast variability in the background part of the image and the subsequent compensation of this variability in the whole image. The application of this method on 33 fundus images showed an average 19% (max. 45%) reduction of luminosity variability and an average 34% (max. 85%) increment of image contrast, with a remarkable improvement, e.g., over low-pass correction. The proposed image normalization technique will definitely improve automatic fundus images analysis but will also be very useful to eye specialists in their visual examination of retinal images.