525.619.8VL - Introduction to Digital Image and Video Processing
Description
This course provides an introduction to the basic concepts and techniques used in digital image and video processing. Two-dimensional sampling and quantization are studied, and the human visual system is reviewed. Edge detection and feature extraction algorithms are introduced for dimensionality reduction and feature classification. High-pass and bandpass spatial filters are studied for use in image enhancement. Applications are discussed in frame interpolation, filtering, coding, noise suppression, and video compression. Some attention will be given to object recognition and classification, texture analysis in remote sensing, and stereo machine vision.
Expanded Course Description
Weekly Schedule:
(Week 01) Introduction to Image Processing and its applications Chapter 1
(Week 02) Two-dimensional sampling theory, quantization, and convolution Chapter 2
(Week 03) Two-dimensional convolution and correlation Chapter 2
(Week 04) Image transforms and their properties Chapter 3
(Week 05) Image enhancement by Histogram modification Chapter 4
(Week 06) Image filtering, image sharpening and noise removal Chapter 4
(Week 07) Image compression MID-TERM EXAM DUE (Take Home) Chapter 6
(Week 08) image segmentation Chapter 7
(Week 09) Edge detection techniques Chapter 7
(Week 10) Feature extraction and representation Chapter 8
(Week 11) Model-based object recognition Notes
(Week 12) Introduction to neural networks for pattern classification Notes
FINAL EXAM (Take Home)
Instructor
Nasser Nasrabadi
Course Structure
The course materials are divided into modules which can be accessed by clicking Modules on the course menu. A module will have several sections including the overview, content, readings, discussions, and assignments. You are encouraged to preview all sections of the module before starting. Most modules run for a period of seven (7) days, exceptions are noted in the Course Outline. You should regularly check the Calendar and Announcements for assignment due dates.
Course Topics
(Week 01)Introduction to Image Processing and its applications Chapter 1 + Notes
(Week 02)Two dimensional sampling theory, quantization and convolution Chapter 2 + Notes
(Week 03)Two dimensional convolution and correlation Chapter 2 + Notes
(Week 04)Image transforms and their properties Chapter 3 + Notes
(Week 05)Image enhancement by Histogram modification Chapter 4 + Notes
(Week 06)Image filtering, image sharpening and noise removal Chapter 4 + Notes
(Week 07)Image compression MID-TERM EXAM DUE (Take Home) Chapter 6 + Notes
(Week 08)image segmentation Chapter 7 + Notes
(Week 09)Edge detection techniques Chapter 7 + Notes
(Week 10)Feature extraction and representation Chapter 8 + Notes
(Week 11) Model-based object recognition Notes
(Week 12)Introduction to neural networks for pattern classification Notes
Course Goals
To understand and describe basic image processing algorithms. To implement image processing algorithms and understand the results.
Course Learning Outcomes (CLOs)
- Describe basic 2-D transforms and be able to implement them.
- Describe edge detection algorithms used in image processing
- Explain histogram equalization technique Describe lossy and lossless compression algorithms Understand and be able to train a simple deep neural network
Textbooks
DIGITAL IMAGE PROCESSING by Rafael C. Gonzalez and Richard E. Woods, (Fourth Edition) Prentice-Hall, 2013, ISBN-13: 978-1292223049, ISBN-10: 1292223049. (not required, recommended)
Other Materials & Online Resources
Course notes for each week will be emailed and avaiable as modules onn the course website.
Student Coursework Requirements
There are 9 HWs all need to be submitted in pdf format to the portal. Each HW carries 100 points. Only two HWs can be sub,itted late.
Grading Policy
Home Works: 30%
Mid-Term Exam: 30%
Final Exam: 40%
Course Policies
Only two HWs are allowed to be submitted late.
Academic Policies
Deadlines for Adding, Dropping and Withdrawing from Courses
Students may add a course up to one week after the start of the term for that particular course. Students may drop courses according to the drop deadlines outlined in the EP academic calendar (https://ep.jhu.edu/student-services/academic-calendar/). Between the 6th week of the class and prior to the final withdrawal deadline, a student may withdraw from a course with a W on their academic record. A record of the course will remain on the academic record with a W appearing in the grade column to indicate that the student registered and withdrew from the course.
Academic Misconduct Policy
All students are required to read, know, and comply with the Johns Hopkins University Krieger School of Arts and Sciences (KSAS) / Whiting School of Engineering (WSE) Procedures for Handling Allegations of Misconduct by Full-Time and Part-Time Graduate Students.
This policy prohibits academic misconduct, including but not limited to the following: cheating or facilitating cheating; plagiarism; reuse of assignments; unauthorized collaboration; alteration of graded assignments; and unfair competition. Course materials (old assignments, texts, or examinations, etc.) should not be shared unless authorized by the course instructor. Any questions related to this policy should be directed to EP’s academic integrity officer at ep-academic-integrity@jhu.edu.
Students with Disabilities - Accommodations and Accessibility
Johns Hopkins University values diversity and inclusion. We are committed to providing welcoming, equitable, and accessible educational experiences for all students. Students with disabilities (including those with psychological conditions, medical conditions and temporary disabilities) can request accommodations for this course by providing an Accommodation Letter issued by Student Disability Services (SDS). Please request accommodations for this course as early as possible to provide time for effective communication and arrangements.
For further information or to start the process of requesting accommodations, please contact Student Disability Services at Engineering for Professionals, ep-disability-svcs@jhu.edu.
Student Conduct Code
The fundamental purpose of the JHU regulation of student conduct is to promote and to protect the health, safety, welfare, property, and rights of all members of the University community as well as to promote the orderly operation of the University and to safeguard its property and facilities. As members of the University community, students accept certain responsibilities which support the educational mission and create an environment in which all students are afforded the same opportunity to succeed academically.
For a full description of the code please visit the following website: https://studentaffairs.jhu.edu/policies-guidelines/student-code/
Classroom Climate
JHU is committed to creating a classroom environment that values the diversity of experiences and perspectives that all students bring. Everyone has the right to be treated with dignity and respect. Fostering an inclusive climate is important. Research and experience show that students who interact with peers who are different from themselves learn new things and experience tangible educational outcomes. At no time in this learning process should someone be singled out or treated unequally on the basis of any seen or unseen part of their identity.
If you have concerns in this course about harassment, discrimination, or any unequal treatment, or if you seek accommodations or resources, please reach out to the course instructor directly. Reporting will never impact your course grade. You may also share concerns with your program chair, the Assistant Dean for Diversity and Inclusion, or the Office of Institutional Equity. In handling reports, people will protect your privacy as much as possible, but faculty and staff are required to officially report information for some cases (e.g. sexual harassment).
Course Auditing
When a student enrolls in an EP course with “audit” status, the student must reach an understanding with the instructor as to what is required to earn the “audit.” If the student does not meet those expectations, the instructor must notify the EP Registration Team [EP-Registration@exchange.johnshopkins.edu] in order for the student to be retroactively dropped or withdrawn from the course (depending on when the "audit" was requested and in accordance with EP registration deadlines). All lecture content will remain accessible to auditing students, but access to all other course material is left to the discretion of the instructor.