From 98febcfe2112c9f00bd25352ef6ba66e7a95e48b Mon Sep 17 00:00:00 2001 From: Daniil Kazantsev Date: Wed, 20 Mar 2019 22:28:28 +0000 Subject: readme update2 --- Readme.md | 4 ---- 1 file changed, 4 deletions(-) (limited to 'Readme.md') diff --git a/Readme.md b/Readme.md index afdbacc..6c45023 100644 --- a/Readme.md +++ b/Readme.md @@ -6,10 +6,6 @@ **Iterative image reconstruction (IIR) methods frequently require regularisation to ensure convergence and make inverse problem well-posed. The CCPi-RGL toolkit provides a set of 2D/3D regularisation strategies to guarantee a better performance of IIR methods (higher SNR and resolution). The regularisation modules for scalar and vectorial datasets are based on the [proximal operator](https://en.wikipedia.org/wiki/Proximal_operator) framework and can be used with [proximal splitting algorithms](https://en.wikipedia.org/wiki/Proximal_gradient_method), such as PDHG, Douglas-Rachford, ADMM, FISTA and [others](https://arxiv.org/abs/0912.3522). While the main target for CCPi-RGL is [tomographic image reconstruction](https://github.com/dkazanc/TomoRec), the toolkit can be used for image denoising and inpaiting problems. The core modules are written in C-OMP and CUDA languages and wrappers for Matlab and Python are provided.** - -
-
-

-- cgit v1.2.3