Quality-Guided Image Denoising for Low-Cost Fundus Imaging

The restoration of noisy images is an essential pre-processing step in many medical applications to ensure sufficient quality for diagnoses. In this paper we present a new quality guided approach for denoising of eye fundus images that suffer from high noise levels. The denoising is based on image sequences and an adaptive frame averaging approach. The novelty of the method is that it takes an objective image quality criteria to assess the different frames and tries to maximize the quality of the resulting image. It can be implemented in an incremental manner which allows real-time denoising. We evaluated our approach on real image sequences captured by a low-cost fundus camera and obtained competitive results to a state-of-the-art method in terms of signal-to-noise ratio whereas our method performs denoising about four times faster.