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Digital Signal and Image Processing
Last Updated: 2026-02-05 15:29:32
Abstract
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.
Objective
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.
Content
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. The course is given in English, but German can also be used for questions during the lectures, for the exercises and at the exams. Week 01: Discrete systems Week 02: Distributions, Linear, shift invariant systems (definition, characterization), convolution, harmonic waves Week 03: LSI description in spatial and frequency domains, the Fourier Transformation Week 04: Properties of the Fourier Transform, symmetries between the spatial and frequency domain, the Convolution Theorem and the Parseval Theorem. Week 05: Sampling, Shannon Theorem, Signal reconstruction Week 06: Interpolation, Quantization, Dithering Week 07: Histogram, intensity transformations, histogram manipulations (equalization and enforcement) Week 08: Finite Impulse Response (FIR) filters, their properties, basic filter types Week 09: Characterization of and design methods for FIR filters in the spatial domain Week 10: Characterization of and design methods for FIR filters in the frequency domain Week 11: Infinite Impulse Response filters in one and two dimensions Week 12: Reconstruction of signals from projections, the Radon transformation
General Information
- Language
- English
- Levels
- BSC , DS , MSC
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- oral 15 minutes
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture | Digital Signal and Image Processing |
|
2 h weekly |
| exercise | Digital Signal and Image Processing |
|
1 h weekly |