Model-based illumination correction in retinal images

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.