This paper evaluates features for assessing digital ophthalmoscopy image quality.
problem Accurate teleophthalmology requires high-quality ophthalmoscopic imagery.
method Statistical metrics, gradient-based metrics, and wavelet transform coefficient derived indicators were tested using machine learning.
result Suitability of features for image quality assessment confirmed, though on a small data set.