signal, signal processing, image processing, filtering, spectrum, Fourier transform
Abstract:
Harmonic signals, their generation. Real signals, sampling theorem, aliasing. Signal filtering. Fourier transform (FT), discrete Fourier transform (DFT), fast Fourier transform (FFT). Spectrum estimation, spectral power density. Image - basic processing methods, 2D Fourier transform, noise filtering, edge detection, linear and non-linear methods, brightness transforms, geometric transforms, image compression.
Objectives:
The goal of the course is to introduce students to the basics of 1D signal processing and image processing. The course is designed so that students are able to apply the acquired information to real data. The output of the course will be the students' own semester project.