Purdue University
School of Electrical and Computer Engineering
Video and Image Processing Program
EE641 Digital Image Processing II
Course Notes
Demonstrations of Algorithms
Class Demos
Introductory Material
Reading List for Course
Introduction
Markov Random Field Short Course Notes
Biomedial Optical Imaging Short Course Notes
1-D Autoregressive Processes
Random Variables and Estimation
Whittening Random Processes
AR Random Processes
Gaussian Random Fields
2-D AR Processes
Noncausal Gaussian Models
Image Restoration using GMRF's and MAP Estimation
Formal Notes
Image Restoration
Page 83 Chapter 2.7 NRC: Conjugate Gradient Method
Mixture Distributions and the EM Algorithm
Formal Notes
Clustering and the EM Algorithm
Markov Chains and Hidden Markov Models
Formal Notes
Markov Chains
Hidden Markov Models and the EM algorithm
Discrete Markov Random Fields
Formal Notes
Discrete MRF Models
viewgraphs,
notes
Simmulation
viewgraphs,
notes
Segmentation using MRF's
Segmentation using MRF's
viewgraphs,
notes
Continuous NonGaussian Markov Random Fields
Continuous NonGaussian MRF's
and MAP image restoration laboratory results
EM Parameter Estimation for 2-D Image Priors
Tomographic Reconstruction
Interative Image Reconstruction
viewgraphs,
notes