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Found 3 papers, 2 papers with code
Direct Unsupervised Denoising
They learn to predict a central tendency of the posterior distribution over possible clean images.
Unsupervised Denoising for Signal-Dependent and Row-Correlated Imaging Noise
Accurate analysis of microscopy images is hindered by the presence of noise.
Image Denoising and the Generative Accumulation of Photons
This new perspective allows us to make three contributions: We present a new strategy for self-supervised denoising, We present a new method for sampling from the posterior of possible solutions by iteratively sampling and adding small numbers of photons to the image.
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