• Corpus ID: 239616142

# Self-supervised denoising for massive noisy images

@article{Wang2021SelfsupervisedDF,
title={Self-supervised denoising for massive noisy images},
author={Feng Wang and Trond R. Henninen and Debora Keller and Rolf Erni},
journal={ArXiv},
year={2021},
volume={abs/2110.11911}
}
• Feng Wang, +1 author R. Erni
• Published 18 October 2021
• Computer Science, Engineering, Physics
• ArXiv
We propose an effective deep learning model for signal reconstruction, which requires no signal prior, no noise model calibration, and no clean samples. This model only assumes that the noise is independent of the measurement and that the true signals share the same structured information. We demonstrate its performance on a variety of real-world applications, from sub-Ångström resolution atomic images to sub-arcsecond resolution astronomy images.

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