Analysis of Image Processing Techniques for Retinal Fundus Images in Detection of Ophthalmic Disease Screening

Retinal image processing is considered as the most important task in detection of ophthalmic disease screening like diabetic retinopathy, diabetic macular edema, glaucoma etc. Automatic detection of these diseases helps doctors to accelerate the process. Preprocessing of the image is the first vital step used in medical imaging due to presence of noise, poor contrast and difference in illumination. This paper focuses on different image pre-processing techniques and their comparative analysis such as Histogram Equalization, Adaptive Histogram Equalization, Contrast Limited Adaptive Histogram Equalization, Median Filter, Speckle Filter and Guassian Filter used for the scanning of retinal fundus images during computer based detection of eye diseases. Performance evaluation of these techniques compared using Entropy, Peak Signal to Noise Ratio.