Each week, you will have on hour of practicals on image processing techniques using MATLAB.

The topics studied will closely follow the structure of the course. The first two weeks will be dedicated to an introduction to MATLAB environment (week 1) and programming (week 2) with examples applicable to image processing. The MATLAB helps and manuals are available online and can also be found in this web page (see link below). You will be expected to work in your spare time to get expertise in MATLAB programming. MATLAB will be part of your assignment. It is a very powerful tool and you will be able to do a lot with it if you put the effort in in the first place. This page will be updated as we progress into the course.

The Program of work is as follows:

• Week1: Introduction to Matlab. Matlab environment. Image handling and display with Matlab.

Available material for week1
Notes:

matlab_w1.doc : week 1 matlab notes

• Week2: Matlab programming. Script, functions and example of programs. Sample programs for Fourier transforms.

Available material for week2:
You can use the four tif images contained in ~ceeyrp/Teaching/225SD2/Images during your investigation. These images include a photographic image (lena), a sonar image (sonar), a synthetic aperture radar image (sar) and a landsat image (landsat). They can be downloaded from here.

Images:

lena.tif sonar.tif



sar.tif landsat.tif

Programs:

fft2d.m : Direct FFT, Display Magnitude and Phase

ifft2d.m : Inverse FFT

invert.m : Inverse of the grey levels of an image


Notes:

matlab_w2doc : week 2 matlab notes

• Week3: Fourier analysis, phase and amplitude analysis of the spectrum. Basic texture descriptors. Image formats. JPEG encoding and DCT transform.

Available material for week3:

Programs:

phase_only.m : Phase Interpretation

random_phase.m : Phase manipulation

random_magnitude.m : Magnitude manipulation

quant_fft.m : Spectrum quantification

move_image.m : Translation using spectrum phase

SimpleFiltering.m : Basic Filtering by spectrum modification

StandardCorrelation.m : Basic Correlation Code

TemplateMatching.m : Template matching code for tutorial 3

Images:

Letters.bmp : Scene for template matching

E.bmp : First template

H.bmp :Second template


Notes:

matlab_w3.pdf : week 3 matlab notes

• Week4: Image enhancement. Histogram equalisation and specification. Basic Histogram based segmentation.

Available material for week4:

Programs:

Otsu.m : Automatic binarisation (thresholding) based on histogram analysis


Notes:

matlab_w4.doc : week 4 matlab notes

• Week5: Filtering. Space domain and frequency domain filtering. Fourier Analysis of filters.

Available material for week5:

Programs:

SimpleFiltering.m Elementary Fourier Filtering

gene_filters.m Various filters generation

Analyse_Filter.m Filter analysis program

deconvolution.m Simple deconvolution example


Notes:

matlab_w5.doc : week 5 matlab notes

 

• Week6: Image Modelling. Fractals #9;.

Available material for week6:


Notes:

matlab_w6.doc : week 6 matlab notes

 

• Week7: Image Modelling. Markov Random field examples.

Available material for week7:

Programs:

generate_MRF_Binomial Quick and dirty MRF generation program (ICM)

generate_MRF.m MRF generation program

generate_MRF_quick.m Quick and dirty MRF generation program (ICM)

denoise_MRF.m Example of denoising using MRF


Notes:

matlab_w7.doc : week 7 matlab notes

 

• Week8: Classification. Basics examples of linear and Bayesian classifiers.

Available material for week8:

You can find here an example of past years assignment. This is not a perfect example and should not be seen as a model! It was in fact judged as slightly too complicated. The notes were also a bit long. The amount of work was adequate however.

On line Ressources

Online Courses
 

• Digital Image Processing by Gonzalez and Woods supporting Web Site
  http://www.imageprocessingbook.com/index_dip2e.htm
  
  
• Hypermedia Image Processing Reference

HIPR - Access from CEE Unix Machimes
HIPR - Access from CEENT Machines
 
Note that due to the licence this is not available through PC-Caledonia


• Digital Image Processing (DIP) with Khoros 2
  http://www.khoral.com/contrib/contrib/dip2001/index.html
  
  
• HIPR2: free www-based set of tutorial materials for the 50 most commonly used image processing operators. It contains tutorial text, sample results and JAVA demonstrations of individual operators and collections.


http://www.dai.ed.ac.uk/HIPR2/
 
• Image Processing fundamentals

http://www.ph.tn.tudelft.nl/Courses/FIP/frames/fip.html
 
•  CVonline: The Evolving, Distributed, Non-Proprietary On-Line Compendium of Computer Vision

http://www.dai.ed.ac.uk/CVonline/
 
• Vision Systems

http://www.cs.cf.ac.uk/Dave/Vision_lecture/Vision_lecture_caller.html

Databases and ressources
 

• Signal Processing Information Base (SPIB)

http://spib.rice.edu/spib.html
 
• efg's Image Processing Page

http://www.efg2.com/lab/library/ImageProcessing/Default.htm
 
• Computer Vision Home Page

Various informations on computer vision, FAQs, Test images, Demos... 
http://www.cs.cmu.edu/afs/cs/project/cil/ftp/html/vision.html


• Pattern Recognition Information

http://www.ph.tn.tudelft.nl/PRInfo.html
 
• Some Internet Resources for Mathematical Modelling

http://www.ifi.uio.no/~matmod/matmod-hotlist.shtml
 
• Wavelet informations

http://www.mathsoft.com/wavelets.html
http://www.wavelet.org/wavelet/links.html
 
• The Face Recognition Home Page

http://www.cs.rug.nl/~peterkr/FACE/face.html
 

Image Processing Applications:

	Improvement of pictorial information for human interpretation
	Processing of scene data for autonomous machine perception

Image Processing Techniques:

	Enhancement
	Process image to give a result that is more suitable than the original for a given application
	Restoration
	Process that attempts to reconstruct or recover an image that has been degraded by using some a priori knowledge of the degradation
	Encoding
	Techniques for representing an image with fewer bits
	Segmentation
	Descriptions of image components rather than whole images
	Understanding
	Symbolically represents contents of an image

Matlab Help Guides

Matlab online help and tutorials can be found here.

The Image processing toolbox online help and tutorials can be found here.

The Image processing toolbox pdf tutorial can be found here.

NOTE: Clipart from http://www.signgray.demon.co.uk/clipart/

This page was adapted from Dr Judith Bell Page. I wish to thank her for her help and support in preparing this course.