A Numerical Tour of Signal Processing

November 11, 2009 by Admin 
Filed under: Computational Geometry, Image processing, Signal Processing, Tutorials 
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Signal Processing

An interesting,  full of pratical examples, tour of signal processing  from  Gabriel Peyré.

Introduction
  1. Basics of Matlab/Scilab Programming
  2. Introduction to Signal Processing
  3. Introduction to Image Processing
  4. Introduction to 2D Wavelet Processing
  5. Introduction to 2D Approximation with Fourier and Wavelets

Wavelet Processing
  1. 1D Haar Wavelet Transform
  2. 2D Haar Wavelet Transform
  3. 1D Daubechies Wavelet Transform
  4. 2D Daubechies Wavelet Transform

Approximation, Coding and Compression
  1. Approximation with Orthogonal Bases
  2. Entropic Coding
  3. Wavelet Image Compression
  4. Wavelets Statistics of Natural Images

Noise and Linear Denoising
  1. Signal and Image Noise Models
  2. Image Denoising with Linear Methods

Wavelet Non-linear Denoising
  1. 1D Signal Denoising with Wavelets
  2. 2D Image Denoising with Wavelets
  3. Advanced Wavelet Thresholdings
  4. Wavelet Block Thresholding
  5. Data Dependent Noise Models

Variational Denoising
  1. Sobolev and TV Denoising
  2. Outliers and Median Denoiser
  3. Non-local Mean

Variational Image Processing
  1. Edge Detection and Heat Diffusion
  2. Total Variation Minimization
  3. Variational Image Segmentation

Audio Processing
  1. Audio Processing with the Short Time Fourier Transform
  2. Audio Separation with Sparsity

Higher Dimensional Signal Processing
  1. Color Image Processing
  2. Color Image Denoising with Median Filtering
  3. Volumetric Data Processing with Wavelets
  4. Video Processing
  5. Multi-spectral Image Processing

Computer Graphics
  1. Texture Synthesis
  2. Fluid Dynamics
  3. Texture Synthesis and Inpainting using Patch Projections

Sparsity and Redundant Representations
  1. Sparse Spikes Deconvolution with Matching Pursuit
  2. Sparse Spikes Deconvolution with Basis Pursuit
  3. Audio Pursuits in a Gabor Dictionary
  4. Dictionary Learning

Inverse Problems
  1. Variational Image Inpainting
  2. Sparse Image Inpainting
  3. Sparse Signal Deconvolution
  4. Reconstruction from Partial Tomography Measurements
  5. Inpainting with NL-means

Compressive Sensing
  1. Sparse Signal Compressed Sensing
  2. Reconstruction from Compressive Fourier Measurements

Numerical Analysis
  1. Wavelet Compression of Integral Operators

Mesh Processing
  1. Basics of 2D Triangulation
  2. Basics of 3D Meshes
  3. Mesh Denoising
  4. Fourier on Meshes
  5. Mesh Parameterization
  6. Mesh Flattening
  7. Mesh Deformation
  8. Wavelets on 3D Meshes (soon available)

Geodesic Processing
  1. Fast Marching in 2D
  2. Fast Marching in 3D
  3. Farthest Point Sampling
  4. Image Compression with Geodesic Triangulation
  5. Anisotropic Fast Marching
  6. Geodesic Computation on 3D Meshes
  7. Shape Matching using the Fast Marching
  8. Geodesic Surface Remeshing (soon available)
  9. Geodesic Bending Invariants (soon available)
  10. Heuristically Driven Propagation (soon available)
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