The diabetic retinopathy (DR) is the leading cause of blindness and occurs when the tiny blood vessels in the retina are damaged. Since DR is a silent disease that may not cause any signs or only cause mild vision problems, it is important to get an eye exam every year so that it can be found early and treated more effectively. Fundus cameras are used to take images of the retina during an eye exam. But for a number of reasons, there is a chance that the images will be blurry and not good enough for a right diagnosis. Because of this, there is a need to improve low-quality images with the right tools. Contrast limited adaptive histogram equalization (CLAHE) is a famous way to improve the quality of a retinal image. In this work, an improved Wiener filter (IWF) is used with the Enhanced CLAHE (ECLAHE) enhancement method to improve the quality of retinal images even more. The IWF can change itself on a local level by tuning its kernel to keep edges and features while reducing noise effectively. Fundus images also have another problem, which is that the lighting isn’t always even. In this study, a method called gamma correction (GC) was used to avoid these kinds of problems. The Local Digital Diabetic Retinopathy (LDDR) database, which is a collection of retinal images, was used to test the benefits of image enhancement. The results were compared with standard CLAHE, Weiner Filter, Gamma Correction, and combination ways of retinal enhancement. Experiments showed that our hybrid method results that were on par with those of the other enhancement methods.