525.674.81 - Image Processing & Analysis
Description
This course provides a comprehensive introductory presentation of the fundamentals of image processing and analysis both from a theoretical and a practical point of view. The course covers fundamental methods for the processing and analysis of images and describes standard and modern techniques for the understanding of images by humans and computers. Topics include elements of visual perception, sampling and quantization, image transforms, image enhancement, color image processing, image restoration, edge detection, image segmentation, and multiresolution image representation. MATLAB exercises demonstrate key aspects of the course. Prerequisites: EN.525.202 (Signals and Systems) , or equivalent, and working knowledge of Matlab.
Instructor
John Goutsias
Course Structure
The course materials are divided into modules which can be accessed by clicking Modules on the course menu on the left. A module has several sections including the overview, content, readings, discussions, and assignments. You are encouraged to preview all sections of the module before starting. Modules run for a period of seven (7) days. You should regularly check the Calendar and Announcements for assignment due dates.
Course Topics
- Image processing and analysis by humans and computers.
- Image processors, Fourier transforms, and sampling.
- Separable image transforms, quantization, compression, enhancement, and noise.
- Image enhancement by histogram equalization/specification.
- Image enhancement by filtering.
- Color image representation and processing.
- Image restoration: mathematical formulation and algebraic methods.
- Image restoration examples.
- Image segmentation by point, line, and boundary detection.
- Image segmentation by thresholding.
- Multiresolution image representation.
- Multiresolution pyramid/wavelet image decomposition schemes.
Course Goals
This class is about techniques for the automatic processing and analysis of images by computers. We begin with an introduction to basic image processing and analysis tasks by humans and computers. We then make the connection to image processing and analysis. We study systems for processing continuous and discrete images both in the space and Fourier domains. We show how to discretize continuous images to put them in a form more appropriate for computers. We then study basic image processing and analysis techniques: image enhancement, restoration, and segmentation. Color images are also considered. Finally, the concept of multiresolution image representation, and its use for image compression, is discussed. The main objective of this course is to provide a comprehensive presentation of the fundamentals of image processing and analysis both from a theoretical as well as practical point of view.
Course Learning Outcomes (CLOs)
- Explain the importance of image processing and analysis in today’s science and engineering applications.
- Apply knowledge of mathematics and signal processing to image modeling, processing, and analysis.
- Make use of algorithms to process and analyze images on computers.
- Process and analyze real images and interpret the results.
- Identify, formulate, and solve specific image processing and analysis problems.
Textbooks
Recommended but not required.
- Gonzalez, R. C., & Woods, R. E. (2019). Digital image processing (4th ed.). Person.
Required Software
Matlab.
You will need access to a recent version of MATLAB. A license is provided at no cost to you, through JHU.
Student Coursework Requirements
Assignments (50%)
First quiz (25%)
Second quiz (25%)
Assignments
All assignments are due according to the dates in the Calendar.
Late submissions may be allowed in special circumstances after prior coordination with the course instructor.
If, after submitting a written assignment, you are not satisfied with the grade received, contact the course instructor.
For information about grading the assignments please refer to the instructions at the end of each assignment.
Quizzes
The first quiz is available in Module 7 and the second quiz is available in Module 14. You will have one week, starting Monday at 12am and finishing Sunday at 11:59pm, to complete each quiz, which will be due by Sunday at 11:59pm exactly one week from its release.
For information about grading the quizzes please refer to modules 7 and 14.
Grading Policy
| Score Range | Letter Grade |
|---|---|
| 100-96 | = A+ |
| 95-90 | = A |
| 89-85 | = A− |
| 84-80 | = B+ |
| 79-75 | = B |
| 74-70 | = B− |
| 69-65 | = C+ |
| 64-60 | = C |
| 59-55 | = C− |
| 54-50 | = D |
| <50 | = F |
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.