EE446 / EE596 Digital Image Processing (3 credits)
Spring 2015
Klipsch School of Electrical and Computer Engineering
College of Engineering
New Mexico State University
Instructor and Class InformationLecture: MWF 1:30 – 2:20pm, T&B 304
Instructor: Dr. Laura Boucheron Office Hours: W 3:00 – 4:00pm,
Goddard Annex 160H F 8:00 – 9:00am,
(575) 6467420 and by prior appointment
lboucher @ nmsu . edu Course Description
Twodimensional transform theory, color images, image enhancement, restoration, registration, segmentation, compression and understanding.
Difference between EE446 and EE596
The undergraduate (EE446) and graduate (EE596) courses are taught simultaneously and cover the same basic material. Assignments and exams will be differentiated such that graduate students will be held to a higher standard than undergraduate students. Higher expectations for graduate students will be in the form of more rigor on the theory and programming problems (which may include additional problems), with a target of 20% more difficulty over the base undergraduate problems. Undergraduate students who wish to complete the graduatelevel
assignments will be awarded extra credit (i.e., up to ~20%). Prerequisite(s)
EE395 Digital Signal Processing or equivalent Strong skills in Matlab programming are expected
Recommended foundation of EE571 Random Processes for EE596 students Textbook
Digital Image Processing, 3rd edition, by Rafael C. Gonzalez and Richard E. Woods (ISBN13: 978013168728 8)
Software
Matlab, including the Image Processing Toolbox, will be required for homework and miniproject assignments. The DSP laboratory is located in T&B 206 and equipped with PCs and MATLAB. Additionally, other computer labs in T&B 202 are also equipped with PCs and MATLAB. The student version of MATLAB can be purchased from the campus bookstore.
Online Resources
Course announcements will be emailed via Canvas and class grades will be posted on Canvas. Canvas email can be forwarded to an alternate email address. The Canvas system can be found at http://learn.nmsu.edu
2. The mathematics behind multidimensional image processing 3. Multidimensional transformation & transformdomain processing 4. Color image acquisition, processing, and display
5. Implementing image processing algorithms on computers in Matlab Contribution to Meeting the Professional Component
EE446 is one of two undergraduate depth electives in digital signal processing, providing three semester hours of engineering topics . Students will apply techniques learned in class through assigned homework (theory and programming problems), algorithm programming, and inclass discussions. This class will provide a broadening of the students' knowledge base to include practical and relevant applications of mathematics and engineering science techniques to the analysis of digital images.
Relationship of the Course to Program Objectives This class addresses the following outcomes:
1. Ability to apply knowledge of mathematics, science and engineering. 2. Ability to design experiments to test and evaluate
3. Ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety manufacturability, and sustainability. 4. Ability to function effectively on teams.
5. Ability to identify, formulate, and solve engineering problems. Americans with Disabilities Act Statement
Section 504 of the Rehabilitation Act of 1973 and the Americans with Disabilities Act (ADA) covers issues relating to disability and accommodations. If a student has questions or needs an accommodation in the classroom (all medical information is treated confidentially), contact:
Trudy Luken
Student Accessibility Services (SAS) Corbett Center, Rm. 244 Phone: 646.6840 Email: sas@nmsu.edu
Website: www.nmsu.edu/~ssd/
Discrimination and Harassment Statement
NMSU policy prohibits discrimination on the basis of age, ancestry, color, disability, gender identity, genetic information, national origin, race, religion, retaliation, serious medical condition, sex, sexual orientation, spousal affiliation and protected veterans status. Furthermore, Title IX prohibits sex discrimination to include sexual misconduct, sexual violence, sexual harassment and retaliation.
For more information on discrimination issues, Title IX or NMSU's complaint process contact: Gerard Nevarez or Agustin Diaz
Office of Institutional Equity (OIE) O'Loughlin House Phone: 646.3635 Email: equity@nmsu.edu
Grading
Homework (30%)– Homework assignments will be posted online and announced in class and encompass both book problems and Matlab programming problems. Let HW Avg, Exam Avg, Project Avg denote homework, exam, and mini project averages respectively. The homework grade, defined as
Homework Grade = min(HW Avg, average(Exam Avg,Project Avg) + 15%)
is worth 30% of the final grade. It is expected solution approaches will be worked out individually, in groups, or with Dr. Boucheron and individual solutions submitted. Depending on the time constraints of the TAs/graders, a subset of homework problems may be selected for grading.
Quizzes (5%)– There will be regular short quizzes based on reading assignments and/or short inclass exercises. Essay(s) (5%)– There will be one or two 12 page essays assigned during the semester to expose students to the societal impacts of image processing technology. In total, the essays will count for 5% of the final grade. Essays will be the work of individual students.
MiniProjects (30% total)– There will be two miniprojects assigned, each worth 15% of the final grade. These projects will require the solution to an image analysis problem to be coded in Matlab and described in a brief report. The topics of these projects will be guided, but the solutions will be openended. It is expected that solutions to the mini projects will be worked out individually and individual solutions submitted.
Exams (30% total)–There will be three exams, each worth 10% of the final grade.
Exam #1 will be held during normal class time. The date will be announced at least one week in advance. Exam #2 will be held during normal class time. The date will be announced at least one week in advance. The Final Exam is scheduled during the Final Exam time, Monday, May 4 from 1:00pm3:00pm.
Graded exams will not be returned to the students. Students are welcome to review their graded exams in Dr. Boucheron's office, but may not make copies or take any notes specific to the exam problems. Exams will be available for review for the duration of the semester and two months after.
Final Grades – Final grades will be assigned as follows (we reserve the right to lower the grade ranges for particular letter grades but will never raise the grade ranges).
A+ >100% C+ (80% , 77%]
A (100% , 93%] C (77% , 73%] A– (93% , 90%] C– (73% , 70%] B+ (90% , 87%] D+ (70% , 67%]
B (87% , 83%] D (67% , 63%]
B– (83% , 80%] D– (63% , 60%] F <60%
Course Policies
Grading Disputes: Disputes regarding homework or exam grades must be submitted in writing to Dr. Boucheron for review within 7 days after graded work has been returned or posted.
Late Assignments: Late assignments are not accepted except in the case of an absence due to a serious medical or other reason. Documentation may be required to verify such an absence. Assignments must be submitted at the beginning of class/lab on they day they are due. In recognition of unforeseen (but not emergency) issues, each student will be issued one “pass” for a late (up to one week) homework submission. These passes are non transferrable and will not be replaced should you lose them. Each unused pass may be submitted at the end of the semester for an extra 1% added to the overall class grade. There will be no passes issued for miniprojects or essay assignments.
Early/MakeUp Exams: No early exams will be given. No accommodations will be made for a missed exam, unless a very serious medical or other situation arose which prevented taking the exam as scheduled.
Documentation will be required to verify such an absence. Accommodations for a missed exam will either 1) result in a reweighting of the other exams to make up for the lost credit or 2) result in a makeup exam being administered at the earliest time possible after the missed exam. The decision of whether to accommodate a documented absence via a reweighting of exam scores or via a makeup exam will be solely at the discretion of Dr. Boucheron.
Academic Dishonesty: Any act of academic dishonesty, e.g., cheating on an exam or copying a homework assignment, may result in an automatic F in the course and/or referral to the Department Head or Dean for disciplinary action. For more information, the NMSU Student Code of Conduct can be found at
http://www.nmsu.edu/~vpsa/SCOC/intro.html
Mobile Devices: Out of respect for the instructor and your fellow classmates, please refrain from use of mobile devices during lecture, and turn off ringers or alarms. Laptops may be used to take notes during the lecture, but should not be used for other purposes (e.g., surfing the web, email). Students who are found to be disruptive will be asked to leave the lecture. Subsequent warnings may include a referral to the Department Head or Dean for
disciplinary action. In the event of an urgent situation requiring that a mobile device be left on during lecture, the student must notify the instructor prior to class, and immediately take the device out of the classroom when taking a call.
Calculators during Exams: Students are encouraged to use a scientific calculator for exams, but may use a graphic calculator only if they refrain from use of the graphing or programming features. Students will sign a statement assuring compliance with this policy on each exam.
EE446/596 Spring 2015 Course Schedule
This schedule is an estimate of the topics covered each week throughout the course. The following chapters are from Digital Image Processing 3/E by Rafael C. Gonzalez and Richard E. Woods (ISBN13: 9780131687288) Week 1 January 12, 2015
Chapter 1: Introduction Week 2 January 19, 2015
Mon., Jan. 19 Martin Luther King Holiday (no class) Chapter 2: Digital Image Fundamentals
Week 3 January 26, 2015
Chapter 2: Digital Image Fundamentals Week 4 February 2, 2015
Chapter 3: Intensity Transformations and Spatial Filtering Week 5 February 9 ,2015
Chapter 3: Intensity Transformations and Spatial Filtering Week 6 February 26, 2015
Chapter 4: Filtering in the Frequency Domain Week 7 February 23, 2015
Chapter 4: Filtering in the Frequency Domain Week 8 March 2, 2015
Chapter 5: Image Restoration and Reconstruction Week 9 March 9, 2015
Chapter 5: Image Restoration and Reconstruction
Week 10 March 16, 2015
Chapter 6: Color Image Processing Week 11 March 23, 2015
Mon.Fri., Mar. 2327 Spring Break (no class) Week 12 March 30, 2015
Fri., Apr. 3 Spring Holiday (no class) Chapter 6: Color Image Processing Week 13 April 6, 2015
Chapter 8: Image Compression Week 14 April 13, 2015
Chapter 9: Morphological Image Processing Week 15 April 20, 2015
Chapter 10: Image Segmentation Week 16: April 27, 2015 Catch up and/or advanced topics Week 17 May 4, 2015
