High-Quality Self-Supervised Deep Image Denoising

NeurIPS 2019 Samuli LaineTero KarrasJaakko LehtinenTimo Aila

We describe a novel method for training high-quality image denoising models based on unorganized collections of corrupted images. The training does not need access to clean reference images, or explicit pairs of corrupted images, and can thus be applied in situations where such data is unacceptably expensive or impossible to acquire... (read more)

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