Comparative study of various image enhancement techniques using performance metrics for effective detection of diabetic retinopathy Available to Purchase

Diabetic retinopathy is a consequence of diabetes which is brought on by high blood sugar levels harming the retina. Patients with diabetic retinopathy start to notice fuzzy vision, color blindness, and variances in vision. Floating dots in vision, night vision deterioration, and dark regions in the visual field when diabetic retinopathy advances to more severe stages. If undetected and mistreated, it can lead to blindness. However, the progression takes years for diabetic retinopathy to endanger your vision. The earliest apparent symptoms of diabetic retinopathy are micro aneurysms, which manifest as tiny red spots on the retina. Other diabetic retinopathy symptoms include hemorrhages, which are red lesions brought on by the rupture of tiny blood vessels in the retina’s deeper layers. Exudates are another type of typical feature of diabetic retinopathy. These lesions are yellow-white and are brought on by plasma leakage from capillaries. Numerous physical examinations, including those for visual acuity, pupil dilation, and optical coherence tomography, can be performed to find diabetic retinopathy, but they take time as well as are costly, and have negative effects on the patients. This paper presents a novel image processing technique and algorithm for the enhancement of eye fundus images for the effective diagnosis of diabetic retinopathy. This paper also highlights the comparison between the effectiveness of different image processing techniques including negative transform, log transform, and contrast stretching techniques. It further compares the various contrast stretching methods including Contrast Limited Adaptive Histogram Equalization (CLAHE), Histogram Equalization (HE), and Adaptive histogram equalization (AHE). The paper concludes with the most effective image processing technique for the diagnosis of diabetic retinopathy that can help to treat the disease in its earlier stages.