Changelog¶
All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog and this project adheres to Semantic Versioning.
v1.0.0 - 2025-05-06¶
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.