CSE 166: Image Processing

Fall 2016

Instructor: Ben Ochoa
Email: bochoa at
Office hours: W 8:00 PM-9:00 PM, EBU3B 3208

TA: Vrinda Gupta
Email: vrg001 at
Office hours: M 9:00 AM-10:00 AM, EBU3B B250A, and Th 2:30 PM-3:30 PM, EBU3B B240A.

Tutor: Dhanesh Pradhan
Email: dpradhan at

Note: when emailing the instructor or TA with questions about the class, please put "CSE 166" in the subject line.

Class section ID: 882388
Lecture: MW 6:30 PM-7:50 PM, CENTR 105
Discussion: F 12:00 noon-12:50 PM, CSB 002
Class discussion: Piazza
Grades: GradeSource

This course covers the foundational topics of digital image processing, including acquisition, filtering, enhancement, restoration, color image processing, multiresolution image representations, compression, morphological image processing, and segmentation.

Prerequisites: Linear algebra and calculus; and data structures.

Programming aspects of the assignments will be completed using MATLAB.

Late Policy: Written homework will be due in class and accepted thereafter with a penalty of 10% per day starting from the due date. Programming assignments will have a hand-in procedure described with the assignment, and also has a 10% per day late penalty. No assignments will be accepted after the graded assignments have been returned or the solutions have been released.

Academic Integrity Policy: Integrity of scholarship is essential for an academic community. The University expects that both faculty and students will honor this principle and in so doing protect the validity of University intellectual work. For students, this means that all academic work will be done by the individual to whom it is assigned, without unauthorized aid of any kind.

Collaboration Policy: It is expected that you complete your academic assignments on your own (or in your own group) and in your own words and code. The assignments have been developed by the instructor to facilitate your learning and to provide a method for fairly evaluating your knowledge and abilities (not the knowledge and abilities of others). So, to facilitate learning, you are authorized to discuss assignments with others; however, to ensure fair evaluations, you are not authorized to use the answers developed by another, copy the work completed by others in the past or present, or write your academic assignments in collaboration with another person. If the work you submit is determined to be other than your own, you will be reported to the Academic Integrity Office for violating UCSD's Policy on Integrity of Scholarship.

Grading: There will be homework assignments, a midterm exam, and a final exam weighted with the following percentages:

Assignments: 50%
Midterm exam: 20%
Final exam: 30%



Lecture topics (tentative):

Required textbook:

Digital Image Processing, 3rd edition
Rafael C. Gonzalez and Richard E. Woods
Pearson, 2008

Last update: November 30, 2016