Course Info Fall 2019

Course Primary Instructor:

Prof. Ghassan AlRegib

Office : Centergy-One Room 5224

E-mail: alregib@gatech.edu

Tel: +1 (404) 894-7005

Course Days/Times: T&TH 1:30-2:45PM

Class Location: KLAUS 1456

Office Hours:

        Tuesdays and Thursdays, 10:15-11:00AM

            I will use BlueJeans for office hours; link can be found on

            Canvas under BlueJeans

         If you prefer to meet in person, let me know.

Communications: No emails whatsoever unless there is an urgent matter. You can send a message to me or to me and the TA using Piazza.

Course Staff:

TBA

                                        

Grading:

Homework*: 25%  Exam #1**:25%   Exam #2**: 25%. Project:25%         

Exams Dates:

        Exam #1:    Tuesday, September 17, 2019

        Exam #2:    Thursday, October 10, 2019

        Final Exam: No Final Exam

* No Homework assignments will be accepted nor graded after the posted due date and time have passed.

** No Make-up exams. If you have to be absent for an exam, you need to inform me in advance with an official justification. An official paperwork is required in all cases.

Due Dates: All Assignments are due on Fridays @5PM; check the outline below. The video students will have an extra 48 hours to turn in their assignments work. The video section will be given a flexible window (typically one week after the Atlanta section’s exam date) to take the exams.

Canvas: All announcements will be posted on Canvas and/or Piazza. Check both sites on a daily basis.

Piazza: Students are expected to utilize PIAZZA platform to post questions and engage into online discussions.

Prerequisite: A course in digital signal processing (ECE4270 or equivalent). I expect students to be familiar with programming.

Course Objective: To introduce the fundamentals and the theory of multidimensional signal processing and digital image processing, key applications in multimedia products and services including machine learning.  

Textbook and References:

No required textbook but the following books are excellent references for this class:

1.     R.C. Gonzalez and R.E. Woods, Digital Image Processing, 3rd edition, Prentice-Hall, 2008 (officially the textbook of the course)

2.     M. Petrou and C. Petrou, Image Processing: The Fundamentals, 2nd Edition, Wiley, 2010 (helpful reference in the first half of the semester)

3.     J. W. Woods, Multidimensional Signal, Image, and Video Processing and Coding, 2nd Edition, Academic Press, 2012

4.     A.K. Jain, Fundamentals of Digital Image Processing, Prentice-Hall, 1989

5.     J.S. Lim, Two-dimensional Signal and Image Processing, Prentice-Hall, 1990

M.J.T. Smith, A. Docef, A Study Guide for Digital Image Processing, Scientific Pub., 1999

Programming Language:

We will utilize Python throughout the course. We have prepared a library called Dippykit to help you perfrom the tasks within the course. Visit https://dippykit.github.io/dippykit/ to get started.

Assignments Submission:  All homework assignments need to be submitted on Canvas. Read the instructions of each assignment carefully.

Attendance: Your attendance and participation are strongly encouraged. There has been a strong correlation between attending lectures and the earned letter grade in this class.

Academic Honesty: All violations of the Georgia Tech Honor Code will be handled by referring the case directly to the Dean of Students for investigation and penalties. The complete honor code can be found in the GT Policy Library: http://www.policylibrary.gatech.edu/student-affairs/academic-honor-code

Available Resources:

·  The Center for Academic Success has programs to help students improve their study habits and time management: http://www.successprograms.gatech.edu/.

·  The Dean of Students Office helps students who have personal or medical issues that impact their academic performance: http://www.deanofstudents.gatech.edu/ 

Office of Disability Services:

If you are a student registered with the Office of Disability Services (ODS), please make sure the appropriate forms and paperwork are completed with the instructor within the first week of classes. The instructor will abide by all accommodations required by ODS. The schedule for exams is posted in the syllabus and any potential modifications or changes will be made with at least one week’s notice. It is the responsibility of the student to properly arrange test accommodations for each exam with ODS in sufficient time to guarantee space for exam administration. ALL exam accommodations must be handled through ODS. If the student does not register accommodations with ODS for the taking of an exam, then they will have to take the exam at the normally scheduled times without any additional accommodation unless the instructor is given specific directive from ODS on the student’s behalf due to a mitigating circumstance.

Travel Dates: I will be attending a number of technical conferences throughout the semester. During these travel times, the Course staff will deliver the lectures, or a pre-recorded video will be shared with the students.

Term Project:

Teams: Students are encouraged to team up in teams of two or three students to work on a term project. A team of one student is not acceptable. A team of more than three students is not acceptable. Utilize Piazza to team up. Each team must designate one member to be in charge of submitting the materials on behalf of the entire team. The other team member(s) should not duplicate submissions.

Topics: The topic of the project is to be chosen by the students. The project must be related to image processing and must focus on one or more of the following applications:

-        Interpolation and Super resolution

-        Image/Video Quality Assessment

-        Image Compression

-        Image Enhancement

-        Saliency Detection in Images or Videos

-        Image Classification

Proposal: On September 20, 2019, every team must submit a one-page proposal that contains the title, the team members names and their GT IDs with their email addresses, a summary of the proposed project, a tentative timeline, and a brief discussion of the expected obstacles. You can list all references in a second page.

Presentation: We will have a certain number of 15-minute slots on November 10, 20, and 21st for teams to sign up for their presentations. We will utilize BlueJeans for all teams including those in Atlanta. Every team will have a total of 15 minutes. The team is expected to present for no more than 7 minutes. The remaining 8 minutes will be kept for Q&A. Every team must make sure their presentation is ready and their Audio and share screen tools are ready before their assigned time slot. Tentatively, the time slots will be between 12pm-3pm on November 19, 20, and 21, 2019. A more exact plan will be shared in the first half of October.  

Term Paper: Every team must turn in a term paper on December 06, 2019. The term paper must follow an IEEE Double-column, single-space, 11-pt font size format. A template can be found HERE.  The term paper must have the following sections:

-        Introduction with motivation and a summary of Prior Art [up to columns]

-        Methodology [between 2~4 columns]

-        Results [between 1~2 columns]

-        Thorough and Detailed Analysis [between 3~6 columns]

-        List of References [ up to 1 column]

The number of columns guidelines per section must be followed.

Project Grade Distribution:

Proposal: 10%

Presentation: 50%

Term Paper: 40%