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

Phone: 650-2524, 2948 e-mail:

Textbook: Digital Image Processing and Analysis: Application with MATLAB and CVIPtools, 3rd Edition, SE Umbaugh, Taylor&Francis/CRC Press, 2018

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.


  • 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


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


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 Matlab or C/C++ to implement the image processing method.

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


Ø Homework is due at the beginning of the first class period the week after assigned; 5 points are earned for working all the problems and one homework problem will be randomly selected from each set to be graded for up to 5 more points (see late policy below)






Overview, Computer imaging systems

Chapter 1


Chapter 2

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

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


Image analysis, preprocessing, CVIPlab

Chapter 3, Sections 3.1, 3.2, 3.4

Chapter 11, as req’d

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

Programming: Introduction to CVIPlab


Human visual system, image model

Electronic Eye Contact, Spectrum Oct09


Chapter 7

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

Program: Spatial filters


Image enhancement, gray scale mods, histogram mod

Chapter 8: Sections 8.1, 8.2.1, 8.2.2, 8.2.3

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

Program: Histogram Modification


Discrete transforms, Fourier

Chapter 5: Sections 5.1, 5.2

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

Supplementary Exercises: 1,2

Program: Fourier transform


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

Chapter 5: Sections 5.3, 5.4, 5.5, 5.6, 5.7

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

Program: Discrete Cosine Transform, Walsh-Hadamard transform, Haar Transform


filtering, wavelet transform, pseudocolor

Chapter 5: Sections 5.8, 5.9 Chapter 8: Section 8.2.4

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

Chap 8: 23,25,27

Not collected due to test


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




Image enhancement, sharpening, smoothing

Chapter 8: Sections 8.3, 8.4 8.5

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

Program: Unsharp masking, Part 1.


Image restoration, overview, system model, noise removal: order filters

Project Proposal Due

Must be approved by Professor

Chapter 9: Sections 9.1, 9.2, 9.3, 9.3.1 Chapter 11: Section 11.4.2

Chap. 9: 1-10

Program: Order filters, Part 1


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

Chapter 9: Sections, 9.3.2, 9.3.3, 9.4, 9.5.1

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



Freq. filters, geometric transforms

Chapter 9: Sections 9.5.2, 9.5.3, 9.5.4, 9.5.4, 9.5.7, 9.6

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



image compression: system model, lossless methods

Chapter 10: Sections 10.1, 10.2.1, 10.2.2

Chap 10: 1-7,10-14



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

Chapter 10: Sections 10.3.1, 10.3.2, 10.3.3, JPEG parts in 10.3.7

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

Not collected due to test



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




Presentation of term project to class, professor and TA

Project Paper Due



Class Attendance Policy: Based on University Class Attendance Policy 1I9: It is the responsibility of students to ascertain the policies of instructors with regard to absence from class, and to make arrangements satisfactory to instructors with regard to missed course work. Failure to attend the first session of a course may result in the student’s place in class being assigned to another student.

Class Policies:  If you have a documented disability that requires academic accommodations, please go to Disability Support Services for coordination of your academic accommodations. DSS is located in the Student Success Center, Room 1270; you may contact them to make an appointment by calling (618) 650-3726 or sending an email to  Please visit the DSS website located online at:  for more information.

Students are expected to be familiar with and follow the Student Academic Code. It is included in the SIUE Policies and Procedures under Section 3C2.2.

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 Students can do their labs using CVIPlab in either C or Matlab

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


TOPICS - reading: Section 2.3, Chapter 11, Appendices, CVIPtools


Chapter 2: Introduction to CVIPlab (MATLAB or C)


Chapter 3: Spatial Filters, parts 1,2,3. Extra credit: parts 4,5,6


Chapter 8: Histogram Modification, parts 1,2. Extra credit: parts 3,4


Chapter 5: Fourier Transform. Extra credit: Filtering, parts 1,2


Chapter 5: Discrete Cosine Transform, Walsh-Hadamard Transform, Haar Transform. Extra credit: Filtering, part 3




(Test #1)


Chapter 8: Unsharp Masking, part 1. Extra credit: parts 2,3.


Chapter 9: Order Filters, part 1, let the user select window size of 3×3 or 5×5, Extra credit: let the user specify any mask size, part 2.

Project proposal due. See Chapter 11: Section 11.4.2

Must be approved by Professor.


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


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. The proposal, due week 10, will include: 1) topic, 2) algorithms to be explored, 3) number and type of images to be used, 4) method of evaluation of results

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

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)/Matlab code to implement related to project
  • 4) Code and debug your function(s), or use CVIPtools
  • 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

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


  • 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)


  • 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