Swarm Based Enhancement Optimization Method for Image Enhancement for Diabetic Retinopathy Detection

A common severe phase of diabetes mellitus known as diabetic retinopathy (DR) results in anomalies on the retina that affect eyesight. The likelihood of visual deterioration will be greatly lowered by early identification and treatment with DR. Because of the complexity of imaging environments, fundus images are usually hampered by noise and poor contrast problems. This study proposes an algorithm for enhancing image quality by lowering noise and enhancing contrast. For the purpose of de-noising and enhancing a color fundus image, the incorporation of proposed Edge Preserving filters and Swarm Based Enhancement Optimization method is implemented. A common public dataset called DIARETDB0 is used to assess the experimental findings. The Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM) which have been measured as 0.000121, 42.37 and 0.999 respectively, are three performance parameters been used. In comparison to other filtering techniques, the suggested algorithm demonstrated improvement in optimizing the quality of images. The tool used for execution is MATLAB.