AIDA.4202 Image Processing

Id: 042977 Credits: 3-3

Description

This course introduces the fundamental principles and techniques of digital image processing, with connections to modern machine learning and deep learning-based vision systems. Topics include image representation, enhancement, filtering, frequency-domain analysis, segmentation, feature extraction, and color processing. Students learn how classical image processing supports, complements, and improves data-driven models in real-world applications. Emphasis is placed on hands-on implementation using Python and critical evaluation of robustness, bias, and ethical considerations. A semester-long project integrates theory with practical image analysis.

Prerequisites

AIDA.3221 Deep Learning.

View Current Offerings

Course prerequisites/corequisites are determined by the faculty and approved by the curriculum committees. Students are required to fulfill these requirements prior to enrollment. For courses offered through online or GPS delivery, students are responsible for confirming with the instructor or department that all enrollment requirements have been satisfied before registering.