3 papers
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…
eess.IV2023
Image Denoising and the Generative Accumulation of Photons
Alexander Krull, Hector Basevi, Benjamin Salmon +5
We present a fresh perspective on shot noise corrupted images and noise removal. By viewing image formation as the sequential accumulation of photons on a detector grid, we show th…