A complexity reduction based retinex model for low luminance retinal fundus image enhancement

AbstractRetinal fundus images play significant roles in the early detection and treatment of various ocular diseases. However, they are often suffered from low luminance in the process of shooting. To address this problem, we propose a Complexity Reduction Retinex (CR\(^2\)) model for the enhancement of low luminance retinal fundus images. The proposed method enables the divided illumination component to be spatially smooth and the reflectance component to be piece-wise continuous. Meanwhile, to improve the computational efficiency, we divide the illumination and reflection components into two independent sub-problems and solve them efficiently by Alternating Direction Minimizing (ADM) method. Comparative results demonstrate that the proposed method outperforms the state-of-the-art methods in terms of qualitative and quantitative evaluations.
Source: Network Modeling Analysis in Health Informatics and Bioinformatics - Category: Bioinformatics Source Type: research