ECE 439 DIGITAL IMAGE PROCESSING SYLLABUS

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

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

Textbook: Digital Image Processing and Analysis: Human and Computer Vision Application with CVIPtools, 2nd Edition, SE Umbaugh, CRC Press, 2011

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; 3 or 4 homework problems will be randomly selected from each set for grading

WEEK

TOPICS

READING

HOMEWORK & LAB

1

Overview, Computer imaging systems

Chap 1: pp. 3-13

Chap 2: pp. 15-68

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

Chap 2: 1,4,17,19,20,21,22,23,26,27

2

Image analysis, preprocessing, CVIPlab

Chap. 3 pp. 77-104,125-127

Chap 11: 715-739

Chap 13: p. 855

Chap 3: 1,2,4,8,9,11,13,14,16,18,19,21

Program: Introduction to CVIPlab. p. 70

3

Human visual system, image model

Electronic Eye Contact, Spectrum Oct09

DisplayRGB_Patterns.pdf

Chap 7: pp. 403-436

Chap 7: 1-9, 11,12,14, 15,16,18,19, 23,25,26,28

Program: Spatial filters, p. 133

4

Image enhancement, gray scale mods, histogram mod

Chap 8: pp. 443-476

Chap 8: 1-7,9,10,14,16,18,20,21,22

Program: Histogram Modification, p. 527

5

Discrete transforms, Fourier

Chap. 5: pp. 259-282

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

Supplementary Exercises: 1,2

Program: Fourier transform, p. 329

6

discrete cosine, Walsh-Hadamard, Haar, PCT, filtering

Chap 5: pp. 282-300

Chap 5: 14-18,20,22,23; Supplementary Exercises: 3,6,7

Program: Discrete Cosine Transform, Walsh-Hadamard transform, Haar Transform, p. 329-330

7

filtering, wavelet transform, pseudocolor

Chap 5: pp. 300-322

Chap 8: pp. 476-489

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

Chap 8: pp. 489-521

Chap 8: 28-40, Suppl Exer: 2,4

Program: Unsharp masking, p. 528, 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 removal: order filters

Project Proposal Due (optional, fyi)

Chap 9: pp. 535-553

Chap 11: pp. 739-742

Chap. 9: 1-10

Program: Order filters, pt 1, p. 630

11

Image restoration: noise removal: mean & adaptive filters, degradation model, inverse filter

Chap 9: pp. 553-582

Chap 9: 11-18, Suppl Exer: 1,3

Project

12

Freq. filters, geometric transforms

Chap 9: pp. 582-603

Chap 9: 19,20,21,23,27,28,33

Project

13

image compression: system model, lossless methods

Chap 10: pp. 637-655

Chap 10: 1-7,10-14

Project

14

image compression: lossy methods, work on project, Oral Presentations.pptx

Chap 10: pp. 657-670, JPEG parts: 684-688, 693-696

Chap 10: 17-21, Suppl Exer: 1,3

Not collected due to test

Project

15

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

 

Project

16

Presentation of term project to class, 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, Chapter 13, App D, CVIPtools

1&2

Introduction to CVIPlab. p. 70

3

Spatial Filters, p. 133, parts 1,2,3. Extra credit: Parts 4,5,6

4

Histogram Modification, p. 527, parts 1,2. Extra credit: parts 3,4

5

Fourier Transform, p. 329

6

Discrete Cosine Transform, Walsh-Hadamard Transform, Haar Transform, p. 329-330

7

 (Study)

8

(Test #1)

9

Unsharp Masking, part 1. Extra credit: parts 2,3., p. 528

10

Order Filters, part 1, let the user select window size of 3x3 or 5x5, p. 630. Extra credit: let the user specify any mask size, and parts 2 & 3.

Project proposal due. See Chap 11: pp. 739-742, Sections 11.5, 11.5.2

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 5 minute presentation of their project in the lab to the class, the professor, and the lab instructor. Do NOT go over 5 minutes and do not have more than 10 PowerPoint slides! Also, an evaluation for each group member will be handed in or emailed with the report.

Ø  In addition to handing in a paper copy of the report, email me a soft copy of the Word file. Before you send me the file give it a meaningful name that includes your last name(s) and the project title.

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

 

http://www.imagescience.org/

Project Paper Format Outline

  • 1. Title page (project title, names, course number, date, etc.)
  • 2. Table of contents with page numbers for: different sections, figures, appendices, etc.
  • 3. Abstract - 1 page or less. Concise description of what is contained in the paper.
  • 4. Introduction/Project overview
  • 5. Body of paper. Broken down into sections as required for you project. For example: Background/theory, experimental methods, discussion and analysis of results, program descriptions, etc. Present results using graphs, images, etc.,
  • 6. Summary and conclusions. Summarize any results and draw conclusions as based on these results.
  • 7. Suggestions for future work. Include any ideas you have based on your work and conclusions about follow-up experiments and/or research.
  • 8. References. Be sure your references are complete. Avoid web sites as references – these come and go – find the source, which is usually a published paper.
  • 9. Appendices - related background information, program listings, etc.

General: reports should be typed, double spaced, pages numbered starting with abstract. Number of pages?- do what is necessary, but keep it concise, extra stuff can go in an appendix. DO NOT put in plastic folder, simply staple in upper left hand corner.

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