Improving Fundus Image Quality for Precision Ophthalmology while Preserving Natural Color Characteristics
DOI:
https://doi.org/10.54228/mjaret0624018Keywords:
Fundus image enhancement; precision ophthalmology; ScatterNet; Natural color preservation; Adaptive gamma correction; Multiscale FilteringAbstract
We present a new unsupervised approach for fundus image quality improvement, particularly suited for precision ophthalmology and the natural colour properties of the retina crucial for diagnosis. We developed a hybrid image enhancement method leveraging complementarity between structure-preserving ScatterNet features, adaptive gamma correction, and multiscale filtering. Our method of enhancement was validated on diverse fundus images under various conditions related to diabetic retinopathy and glaucoma. Results show that our method increases image contrast by 35%, increases edge preservation by 25%, and boosts colour fidelity by 40% compared with conventional enhancement methods. Moreover, in general, the proposed method can increase PSNR values on average by 30%. Our method has an intended use to enhance image quality for ophthalmologists to make more accurate diagnoses, while retaining the natural appearance of retinal features.
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