Course Description

This is an undergraduate course the basics of image processing. Topics covered will include concepts from two-dimensional signal processing (e.g., 2D Fourier transforms, z-transforms, etc.) including image filtering/restoration, edge detection, segmentation, image analysis, image compression, and image reconstruction.

Course Information

Lectures: Mondays/Wednesdays 11:00 – 12:20 in Jacobs Hall (EBU1), Room 2315
Discussions: Wednesdays 09:00 – 09:50 in Warren Lecture Hall (WLH), Room 2206

Syllabus: on Canvas

Instructor: Rahul Parhi (rahul@ucsd.edu)
Office: Jacobs Hall, Room 6406
Office Hours:
       Thursdays 16:00 – 17:00
       Fridays 16:00 – 17:00

TA: Luke McDermott (lmcdermo@ucsd.edu)

Canvas: https://canvas.ucsd.edu/courses/75498
Piazza: https://piazza.com/class/mnc8zwk08kk289

Prerequisites

This course assumes basic knowledge of linear systems fundamentals at the level of ECE 101 or 161A. Some background in probability will be helpful (e.g., at the level of ECE 109). Familiarity with Python will be necessary for the programming components of the course.

Course Grade

The course grade will be determined by

• 6-8 Assignments (either “pen-and-paper” homework or programming lab exercises) (20%)
• Midterm Exam (40%)
  • The midterm will take place on May 4, 2026 in class
• Final Exam (40%)
  • The final will take place on June 3, 2026 in class

Academic Integrity

UCSD’s Code of Academic Integrity applies to this course. It is dishonest to cheat on exams, copy other people’s work, or fake experimental results. An important element of academic integrity is fully and correctly acknowledging any materials taken from the work of others. Instances of academic dishonesty will be referred to the Office of Student Conduct for adjudication.