Digital Image Processing Fall 2005 - Course Syllabus Professors/Course Coordinators: Dr. Rahman Tashakkori (ASU) email: mailto:rt@cs.app.edustat, Dr. Suzanne Lea (UNCG) email: smlea@uncg.edu, Dr. Mark Holliday (WCU) email: holliday@email.wcu.edu

Office: CAP 121, Office Phone: 262-7009 Office Hours: MWF 8:00-10:00,  MW 2:00-3:00, T 8:00-10:00, and Open Door Policy. Online office hours will be decided at the beginning of the semester. Class Time/Location: MWF 1:00-1:50 Room 246 CAP and over the NCREN at the remote sites Final Exam: Thursday, December 8, 2005 Noon-2:30 PM

Course Description This course is an introduction to Digital Image Processing.  It is designed to cover digital techniques for image representation, enhancement, compression and restoration. The course is intended for the first year graduate and upper level undergraduate students.

Some of the Topics Introduction Mathematical Background Fundamentals Intensity Transformations and Spatial Filtering Frequency Domain Processing Image Restoration Color Image Processing Image Compression

Prerequisite Computer Science - II and Linear Algebra It is helpful to have a background in digital signal processing and statistics. Required Texts R. Gonzalez, R. Woods, and S. Eddins, Digital Image Processing using MATLAB, Prentice Hall, Additional readings will be posted on the web page of the course. Another Reference: Image Processing Toolbox manual by MathWorks Inc.  The pdf file will be made available to you for class use.

Grading Policy The following grading scale will used in this course:      Exam (1) and (2), 15% (each),      Final exam, 25%,      Assignments and Labs 15%,      Individual Research Papers and Projects %20.      Quizzes and class participation %10.

Grading Scale A = 90 to 100 B = 80 to 89 C = 70 to 79 D = 60 to 69 F = Below 60

Attendance and Academic Integrity Students are required to attend all classes.  Each unexcused absence will result in a 3 point drop from the final grade.  Students with more than 8 absences will fail the course.  No make-up exams will be given in this course.  If you missed an exam due to an "extreme circumstances" such as illnesses, death of a relative, or problems of this nature, you have to present documents (e.g. a letter from a doctor, a letter from a hospital, or an obituary from the funeral).  In such cases, student's final exam's grade will be used for the missed exam.

All assignments are due before the start of the class on the due date All assignments are due before the start of the class on the due date. No assignment will be accepted once the solution is discussed in the classroom.  All assignments and programs MUST be completed by students individually unless the assignment or project is given as a team project.  In such a case, the team members can work together on the project.  You may discuss the assignments and programs among each other but you have to write/edit programs by YOURSELF.   Please see the ASU Academic Integrity Policy for a description of the woes that befall a transgressor!

Note to students at the remote sites: Please send me an e-mail (rt@cs.appstate.edu) containing: Your complete name: What name do you wish me to call you in class: Your classifications (senior, junior,…): Your IM screen name (I use Windows Messenger r_tashakkori@hotmail.com to contact you) Have you statistics course? Programming language of your choice: Do you have access to MATLAB: Briefly explain if you have had any experience with image processing: