Diagnosing wider disease in retina is more significant in Ophthalmology. Using Image processing techniques to identify the retinal diseases has proven more precise than other technology implementations, rapidly. Certain disorder identifications lowers the quality with respect to the limiting capacities and diagnosing them. Irrespective of several algorithms and researches the issue remains unsolved on the retinal disease identifications using image processing. Where huge number of observations turned negative with retinal color images, which in turn formulated an enhanced technique that is solely focuses on the green component of the retinal image. Corona virus spread during the year 2019 is predicted to have allied with the variations in the nerve vessel, that is seen into the partitioned eye fundus with the patients in the process of detecting the variations in the retinal via image processing which is also used to assess the potential correlation over medical constraints.Initially, the retinal image of the eye is pre-processed which is further processed by identifying the presence of the pictorial particulars using contrast improvisation and histogram equalization, CLAHE. Secondly by removing the noise from the image, using WMF (www mmmm ffff). Upon comparison with filters like median, wiener etc., WMF is proved to be the best from the results obtained in this proposed research work. Finally, retinal images were segmented with the nerve cells in the retinal images of Covid-19 infected individuals using SOBCAN (SSSooobbb ccc aaa nnn) methodology. The fundus images and performance was evaluated based on parameters including MSE, PSNR and SSIM. The results were compared with other technologies like sobel, canny etc., and concludes that the proposed methods’ formulated outcome outperforms the equivalent enhancement method.