Digital Signal and Image Processing

Dr. Sven Hirsch and Prof. Gabor Székely

Lectures and Exercises
Friday, 13-16 hrs, CAB H56
Course Material

Objective:The lecture provides an introduction to basic methods of digital image signal processing covering the following major topics: linear shift invariant systems and their characterization, the Fourier transform, signals in the spatial and frequency domain as well as sampling, quantization and interpolation. Theoretical and implementational issues about 1D and 2D FIR and IIR filters are also discussed.

Contents: The goal of the lecture is to provide an introduction to basic knowledge and methods of signal processing, which is necessary to follow subsequent courses in visual computing (like computer graphics, computer vision or pattern recognition). While mostly concentrating on the processing of higher dimensional signals (2D, 3D), the course will be self-contained and discusses the underlying concepts also for the 1D (time-dependent) case. Only basic concepts of real and complex analysis and probability theory will be assumed to be known.

Prerequisites: Basic concepts of mathematical analysis and linear algebra. The computer exercises are based on UNIX and C. The course is given in English, but German can also be used for questions during the lectures, for the exercises and at the exams.

Course material: Script, computer demonstrations, exercises and problem solutions.