Due to several patient dependent and camera dependent factors which are difficult to control in a color retinal imaging setup, non-uniform luminosity and contrast variability is observed within and across images. Most algorithms for lesion detection are highly dependent on the local image intensity and contrast and hence tend to suffer if there is significant variability. Therefore, image preprocessing for illumination correction and contrast enhancement is a crucial step in any scheme for automated detection of diabetic retinopathy in retinal images. Noise at the pixel level is also a major problem as it gets amplified in a contrast stretch operation. This necessitates an image smoothing operation. Here, we used a complex diffusion based shock filter for image smoothing and contrast enhancement. Complex shock filter is a non-linear forward-backward diffusion based approach for image enhancement proposed by Gilboa et al. Shock filtering the image results in removal of speckle noise, reduces JPEG compression artifacts and also acts as an effective adaptive contrast enhancement scheme. The application of our method on the DIARETDB1 database, and a local database shows that it outperforms existing image enhancement methods. © 2013 Springer-Verlag.