This is the R collection. For complete Python walkthroughs, visit the Python tours. All language archives →
These are the R tours, that can be browsed as HTML pages, but can also be downloaded as Jupyter notebooks. Please read the installation page for more information about how to run these tours.
Basics
- Introduction to Image Processing
- Le traitement numérique des images
- Image Approximation with Fourier and Wavelets
Wavelets
Approximation, Coding and Compression
Denoising
- Linear Image Denoising
- Wavelet Denoising
- Wavelet Block Thresholding
- Non Local Means
- Rank Filters for Image Processing
Inverse Problems
- Image Deconvolution using Variational Method
- Inpainting using Sparse Regularization
- Performance of Sparse Recovery Using L1 Minimization
Optimization
- Gradient Descent (by Laurent Condat)
- Forward-Backward Splitting (by Laurent Condat)
- Forward-Backward method on the dual problem
- Douglas Rachford Proximal Splitting
- Chambolle-Pock Primal-Dual Splitting Algorithm
Machine Learning
- PCA, Nearest-Neighbors and Clustering
- Linear Regression and Kernel Methods
- Logistic Classification
- Stochastic Gradient descent
Shapes
- Edge Detection
- Active Contours using Parameteric Curves
- Active Contours using Level Sets
- Manifold Learning with Isomap