Kursinformation

Lehrinhalte
A Basics
[list]
[*]Scene Representation2D and 3D Geomtery
[*]Image Acquisition
[list]
[*]Geometric Projections Camera Calibration
[/list]
[*]Objective and Illumination
[*]Discrete 2D signals
[list]
[*]Separability, Sampling
[*]Transformation, Interpolation
[*]Convolution, Correlation
[*]Discrete Fourier Transformation
[/list]
[/list]
B Basics of Image Analysis
[list]
[*]Filtering
[list]
[*]Basics2D Filter Design
[*]Linear Filtering
[*]Nichtlinear Filtering
[/list]
[*]Image Decompositions
[list]
[*]Multi-scale Representation
[*]Pyramids
[*]Filter Banks
[/list]
[*]Image Features
[list]
[*]Structure
[*]Moments, Histograms
[/list]
[/list]

Literature
References / Textbooks: Lecture slides, exercise sheets and matlab-code.
Further reading
[list=1]
[*]Yi Ma, Stefano Soatto, Jana Kosecka und Shankar S. Sastry, An Invitation to 3-D Vision - From Images to Geometric Models, Springer, 2003.
[*]Richard Hartley and Andrew Zisserman, Multiple View Geometry in Computer Vision, Second Edition, Cambridge University Press, 2004.
[*]Karl Kraus, Photogrammetrie, Band 1 Geometrische Informationen aus Photographien und Laserscanneraufnahmen 7. Auflage, de Gruyter Lehrbuch, 2004.
[*]Christopher M. Bishop, Pattern Recognition and Machine Learning, Springer 2006.
[*]Bernd Jähne, Digital Image Processing, 6. Auflage, 2005.
[/list]