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cs.CV2023
Direct Unsupervised Denoising
Benjamin Salmon, Alexander Krull
Traditional supervised denoisers are trained using pairs of noisy input and clean target images. They learn to predict a central tendency of the posterior distribution over possibl…
eess.IV2023
Unsupervised Denoising for Signal-Dependent and Row-Correlated Imaging Noise
Benjamin Salmon, Alexander Krull
Accurate analysis of microscopy images is hindered by the presence of noise. This noise is usually signal-dependent and often additionally correlated along rows or columns of pixel…