Restoration of retina images using extended median filter algorithm

Abstract

Diabetic Retinopathy is one of the complicated diseases and it is caused by the changes in the blood vessels of the retina. Extraction of retina image through Fundus camera sometimes produces poor contrast and noises; detection of blood vessels in the retina is very complicated. So preprocessing is needed, in this paper a novel algorithm is implemented to remove the noisy pixel in the retina image. The proposed algorithm is Extended Median Filter and it is applied to green channel of the retina, because green channel vessels are brighter than the background. Proposed extended median filter is compared with the existing standard median filter by performance metrics such as Peak Signal-to-Noise Ratio, Mean Square Error and Root Mean Square Error. Experimental results show that the proposed Extended Median Filter algorithm gives better result than the existing standard median filter in terms of noise suppression and detail preservation.

Classification of visualization exudates fundus images results using support vector machine

“…The retina is a light-sensitive layer at the back of the eye. The retina changes the light into nerve signals and transmits it to the brain via the optic nerve [18][19]. DR is one of the diseases in the retina which caused several abnormalities such as microaneurysms, exudates, macular edema and hemorraghes.…”