auto-denoise - Release version 1.0.0

This is the first major release of Auto-denoise, providing initial implementations for a small selection of unsupervised and self-supervised CNN denoising methods. These methods currently include:

• Noise2Noise (N2N) - A self-supervised denoising method using pairs of images of the same object.
• Noise2Void (N2V) - A self-supervised denoising method capable of working with a single image. We have also implemented a later development of the method that can work with structured noise.
• Deep Image Prior (DIP) - An unsupervised denoising/upsampling/deconvolution method that can also work with a single image.
• Supervised denoising methods, and the tomography-specific Noise2Inverse (N2I) method.

We also provide a small set of pre-configured models for these algorithms: U-net, MS-D net, DnCNN, and a custom ResNet implementation.

Full Changelog: https://github.com/CEA-MetroCarac/auto-denoise/compare/v0.0.0...v1.0.0

- Python
Published by Obi-Wan about 1 year ago