Image Denoising and the Generative Accumulation of Photons | Alexander Krull
Автор: Intelligent Medical Systems
Загружено: 2023-11-20
Просмотров: 434
Abstract
Shot noise is a fundamental property of many imaging applications, especially in fluorescence microscopy. Removing this noise is an ill-defined problem since many clean solutions exist for a single noisy image. Traditional approaches aiming to map a noisy image to its clean counterpart usually find the minimum mean square error (MMSE) solution,i.e. , they predict the expected value of the posterior distribution of possible clean images. 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 that a network trained to predict the where the next photon could arrive is in fact solving the traditional MMSE denoising task. This new perspective allows us to make three contributions:
(i) We present a new strategy for self-supervised denoising. (ii) 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. (iii) We derive a full generative model by starting this process from an empty canvas."
https://www.dkfz.de/en/datascience/se...
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