Abstract
Retinal 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.
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Acknowledgements
This work is supported by the National Natural Science Foundation of China (No. 61801272) and National Natural Science Foundation of Shandong Province (Nos.ZR2021QD041 and ZR2020MF127).
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Li, X., Gao, M., Shang, J. et al. A complexity reduction based retinex model for low luminance retinal fundus image enhancement. Netw Model Anal Health Inform Bioinforma 11, 30 (2022). https://doi.org/10.1007/s13721-022-00373-3
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DOI: https://doi.org/10.1007/s13721-022-00373-3