CMSC 465 - Image and Signal Processing

Description
Prerequisites: MATH 141 and CMSC 350. A project-driven study of image and signal processing. The goal is to apply spectral analysis techniques to analyze time series data for the purpose of recognizing and classifying signals and to apply image segmentation, representation, and description techniques to recognize and classify objects. Topics include discrete Fourier transforms, fast Fourier transforms, sampling and filtering, and image transformations and enhancements. Enrollment Requirements: Prerequisite: MATH 141 and CMSC 350.
Credits
3
Recent Professors
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Recent Semesters
Spring 2020, Fall 2019, Spring 2019, Fall 2018, Spring 2018
Avg. Sections
1