Retinal Image Quality Enhancement and Retinal Vessel Segmentation with Implementation of Color Dominance and Boosted Remora Optimization Algorithm with Deep Adversarial Approach (CDBROA)

The main reason for ocular deficiency is diabetic retinopathy, which is prevalent among people aged 25–74, significantly affecting health care and socioeconomic systems. Early detection can prevent vision loss in nearly 90% of cases, but retinal fundus images often suffer from noise and poor illumination, limiting automated analysis. This study proposes an integrated image enhancement and classification framework using Lab color-space enhancement, Wiener filtering, adaptive fuzzy Tsallis entropy segmentation, and curvelet-based feature extraction. The proposed color dominance and boosted Remora optimization algorithm with deep adversarial approach achieved high accuracy, precision, sensitivity, and robustness on a retinal fundus dataset.