a comparative study on preprocessing techniques in diabetic retinopathy retinal images: illumination correction and contrast enhancement

to investigate the effect of preprocessing techniques including contrast enhancement and illumination correction on retinal imagequality, a comparative study was carried out. we studied and implemented a few illumination correction and contrast enhancementtechniques on color retinal images to find out the best technique for optimum image enhancement. to compare and choose thebest illumination correction technique we analyzed the corrected red and green components of color retinal images statistically andvisually. the two contrast enhancement techniques were analyzed using a vessel segmentation algorithm by calculating the sensitivityand specificity. the statistical evaluation of the illumination correction techniques were carried out by calculating the coefficients ofvariation. the dividing method using the median filter to estimate background illumination showed the lowest coefficients of variationsin the red component. the quotient and homomorphic filtering methods after the dividing method presented good results basedon their low coefficients of variations. the contrast limited adaptive histogram equalization increased the sensitivity of the vesselsegmentation algorithm up to 5% in the same amount of accuracy. the contrast limited adaptive histogram equalization techniquehas a higher sensitivity than the polynomial transformation operator as a contrast enhancement technique for vessel segmentation.three techniques including the dividing method using the median filter to estimate background, quotient based and homomorphicfiltering were found as the effective illumination correction techniques based on a statistical evaluation. applying the local contrastnhancement technique, such as clahe, for fundus images presented good potentials in enhancing the vasculature segmentation.