ECE 439 DIGITAL IMAGE PROCESSING SYLLABUS

Professor: Dr. Scott E Umbaugh  Office: Engineering Building, Room EB3037

Phone: 650-2524, 2948 e-mail: sumbaug@siue.edu

Textbook: Computer Imaging: Digital Image Analysis and Processing , SE Umbaugh, CRC Press, 2005

Prerequisite: ECE 351 and programming experience, or consent of instructor

Class Format: Two lectures and 1 lab/homework per week, two tests, quizzes and term project

Web Site Imaging Examples: CVIPtools Imaging Examples

Goals and Objectives: Introduce the student to analytical tools and methods which are currently used in digital image processing as applied to image information for human viewing. Then apply these tools in the laboratory in image restoration, enhancement and compression.

COURSE OUTLINE

  • Image Sensing and Representation, 2 Lectures, Chapter 1, 2
  • Image Analysis, CVIPlab, 2 Lectures, 3.1, 3.2, 11
  • Human Visual Perception, 2 Lectures, Chapter 7
  • Image Enhancement, 2 Lectures, Sections 8.1, 8.2
  • Image Transforms, 6 Lectures, Chapter 5

TEST #1

  • Image Enhancement, 3 Lectures, Sections 8.3, 8.4
  • Image Restoration, 4 Lectures, Chapter 9
  • Image Compression, 4 Lectures, Chapter 10

TEST #2

PROJECT DUE -- 16th week

Project will be some application of image enhancement, restoration or coding/compression technique to digital image(s). Software will be written in the C programming language to implement the image processing method.

GRADING: Test #1 - 25%, Test #2 - 25%, Homework & Lab Exercises - 25%, Project - 25%

ECE 439 LECTURE SCHEDULE

Ø    Homework is due the first class period the week after assigned; 4 homework problems will be randomly selected from each set for grading

WEEK

TOPICS

READING

HOMEWORK & LAB

1

Overview, Computer imaging systems

pp. 3-11, 15-57

Chap 1: 1,2,3,4,5,6

Chap 2: 1,4,19,20,21,22,23,27

2

Image analysis, preprocessing, CVIPlab

pp. 67-93, 551-573

Chap 3: 1,2,4,8,9,11,13,16

Program: 2.7.1

3

Human visual system, image model

pp. 313-336

Chap 7: 1-9, 11, 14,16,18,19

Program: 3.6.1, parts 1, 2 (zero-order only), 3, 5

4

Image enhancement, gray scale mods, histogram mod

pp. 341-371

Chap 8: 1-7,10,14,16,20,21,22

Program: 8.7.4, parts 1,2

5

Discrete transforms, fourier

pp.  201-220

Chap 5: 1-8, 11,12,13,21

Program: 5.11.2

6

discrete cosine, walsh-hadamard, Haar, PCT, filtering

pp. 220-231

Chap 5: 14-18,20

Program: 5.11.3, 5.11.4, 5.11.5

7

filtering, wavelet transform, pseudocolor

pp. 231-252, 371-377

Chap 5: 9,10,19,24-27,30-36

Chap 8: 23,25,27

Not collected due to test

8

Review and TEST #1, Study Guide, 439SAMPLEtst1.doc , Sample Test KEY

 

 

9

Image enhancement, sharpening, smoothing

pp. 377-391

Chap 8: 28-40

Program: 8.7.9, part 1. You can use CVIPtools functions such as: hist_stretch, subtract_Image, specify_filter, convolve_filter,

mean_filter, smooth_filter

You CANNOT use unsharp_filter

10

Image restoration, overview, system model, noise

Project Proposal Due

pp. 407-421

Chap. 9: 1-10

Program: 9.9.2, part 1

11

Image restoration: noise removal, degradation model, inverse filter

pp. 421-441

Chap 9: 11-17

Project

12

Freq. filters, geometric transforms

pp. 441-460

Chap 9: 18-21,23,27,28,32

Project

13

image compression: system model, lossless methods

pp. 481-498

Chap 10: 1-6,10-13

Project

14

image compression: lossy methods, work on project

pp. 500-513, JPEG parts: 524-533

Chap 10: 17-21

Not collected due to test

Project

15

Review and TEST #2 ,Study Guide,  439SAMPLEtst2.doc , Sample Test Key

 

Project

16

Demo term project to professor and TA

Project Paper Due

 

 

ECE 439 Digital Image Processing Lab Outline

Ø    Homework and program listings will be handed in at the beginning of the first class period the week after assigned

Ø   Late homework and lab work is worth 50% up until 2 days late, after that it is worth 10%

Ø    Useful document for those familiar with C++, but not C programming: C for C++ Programmers.htm

Week

TOPICS - reading: Section 2.3, Chapter 11, CVIPtools

1&2

2.7.1 Introduction to CVIPlab

3

3.6.1 Image geometry operations, parts 1, 2: zero-order only, 3, and 5. Extra credit: Part 2: first order, parts 4, 6 and 7.

4

8.7.4 Histogram modification, parts 1,2. Extra credit: parts 3,4

5

5.11.2 Fourier transform

6

5.11.3 DCT, 5.11.4 WHT, 5.11.5 Haar transforms

7

 (Study)

8

(Test #1)

9

8.7.9 Unsharp masking, part 1. Extra credit: parts 2,3.

10

9.9.2 Order Filters, part 1, 3x3 only. Extra credit: let the user specify mask size, and part 2.

Project proposal due.

11-15

Work on project: application of image enhancement, restoration or coding/compression.

16

Present project to the class

 

ECE 439 Digital Image Processing - Semester Project

Semester Project: The project will consist of designing experiments, implementing algorithms, and analyzing the results for an image processing problem. You should work in groups of 2. The project will be selected by the students, subject to approval by the professor. A paper will be written describing the project and discussing what was learned during the project. The final paper should be about 8 to 15 pages, typed and double-spaced; include images ! In the paper include an appendix containing program listing(s). The students will give a short presentation of their project in the lab to the class, the professor, and the lab instructor.

Grading: The project is worth 25% of your term grade, broken down as follows:

  • Overall Project.. 15%
  • Paper................. 5%
  • Presentation........ 5%

Due Dates

Ø      Week 10:  Brief, 1 page max., project proposal (this is optional and is for your benefit)

Ø      Week 16 (Finals week): Project paper due. Presentation//demo (finals week)

Suggested Project Process:

  • 1) Find an area of interest from the lab or from class; see Section 11.5.2 in textbook for project ideas.
  • 2) Design experiment(s) you wish to pursue
  • 3) Design algorithms/C function(s) to implement related to project
  • 4) Code and debug your function(s)
  • 5) Test your functions on some real images
  • 6) Process images/do the experiments
  • 7) Compare and contrast your results to other similar results from using CVIPtools functions, or research results in library from similar experiments - Analyze results using appropriate metrics, tabulate or plot, etc. Use the objective and subjective fidelity measures in Chapter 7 to compare images. Design your subjective measure experiments carefully as outlined in Chapter 7.
  • 8) Write report, include images
  • 9) Present/demo to the class

·  NOTE: If you do not have any specific images that you want to use, take a look at the image databases on the Internet, such as:

DIP Image Databases

Brief Bibliography

Books

·         1a. Computer Vision and Image Processing: A Practical Approach Using CVIPtools - S. E Umbaugh, Prentice Hall PTR, Upper Saddle, NJ, 1998

  • 1. Digital Image Processing - R.C.Gonzalez & P.Wintz
  • 2. Robot Vision - B.K.P.Horn
  • 3. Computer Vision - D.H.Ballard & C.M.Brown
  • 4. Syntactic Pattern Recognition : An introduction -R.C.Gonzalez and M.G.Thomason
  • 5. Pattern Recognition - A Statistical Approach - P.A. Devijver and J. Kittler
  • 6. Digital Image Processing - W. K. Pratt
  • 7. Fundamentals of Digital Image Processing - A.K. Jain
  • 8. Digital Picture Processing - A. Rosenfeld and A.C. Kak
  • 9. Pattern Classification and Scene Analysis - R.O. Duda and P.E. Hart
  • 10. Object Recognition by Computer - W.E.L. Grimson
  • 11. Digital Pictures - A.N. Netravali and B.G. Haskell
  • 12. Vision in Man and Machine - M.D. Levine
  • 13. Pattern Recognition Statistical, Structural and Neural Approaches, R.J Schalkoff, John Wiley & Sons NY
  • 14. Digital Image Processing and Computer Vision, R.J. Schalkoff, Wiley
  • 15. Artificial Intelligence: An Engineering Approach, R.J. Schalkoff, McGraw-Hill
  • 16. Algorithms for Graphics and Image Processing, Theo Pavlidis, Computer Science Press, call no.: T385.P381982
  • 17. Handbook of Pattern Recognition and Image Processing, K.S. Fu and T.Y. Young, Academic Press
  • 18. The Image Processing Handbook, John C. Russ, CRC Press SIUE Library call #: TA1632.R881992 (reference)

Journals

  • 1. IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2. IEEE Transactions on Computers
  • 3. Pattern Recognition
  • 4. Computer Vision, Graphics and Image Processing
  • 5. IEEE Transactions on Medical Imaging
  • 6. Computerized Medical Imaging and Graphics
  • 7. IEEE Transactions on Image Processing
  • 8. IEEE Engineering in Medicine and Biology
  • 9. IEEE Transactions on Signal Processing
  • 10. IEEE Transactions on Neural Networks
  • 11. IEEE Transactions on Geoscience and Remote Sensing
  • 12. Photogrammetric Engineering and Remote Sensing
  • 13. International Journal of Remote Sensing
  • 14. Journal of Visual Communication and Image Representation

Numerous Conference Proceedings from the following professional groups:

  • IEEE - Institute of Electrical and Electronic Engineers
  • SPIE - Society of Photographic and Instrumentation Engineers, The International Society for Optical Engineering
  • SMPTE - The Society of Motion Picture and Television Engineers
  • PRS - Pattern Recognition Society