A review: Comparison between different type of filtering methods on the contrast variation retinal images

Retinal images are obtained using a fundus camera in order to evaluate many important diseases such as Diabetic Retinopathy and Glaucoma. Sometimes, the images appear as uniformly illuminated, have luminosity and contrast variability. This problem can be severely compromised the diagnostic process and the results, especially if automated computer-based procedure is used to derive the parameters of diagnostic. Many researchers propose different approaches to normalize the badly illuminated images based on filtering techniques. In this paper, we compare a six (6) type of filtering techniques and applied to the retinal images from Digital Retinal Images for Vessel Extraction (DRIVE) database to adjust the contrast variation and illumination in order to produce a better diagnostic result. The result performance is evaluate based on Signal Noise Ratio (SNR) and Mean Square Error (MSE) is compared to the other filtering methods. From the result, the Homomorphic filtering based on high pass filter obtained higher SNR value which is 3.093 and the lowest in MSE which is 71267.51.