Lehrinhalte
A Basics
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[*]Scene Representation2D and 3D Geomtery
[*]Image Acquisition
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[*]Geometric Projections Camera Calibration
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[*]Objective and Illumination
[*]Discrete 2D signals
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[*]Separability, Sampling
[*]Transformation, Interpolation
[*]Convolution, Correlation
[*]Discrete Fourier Transformation
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B Basics of Image Analysis
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[*]Filtering
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[*]Basics2D Filter Design
[*]Linear Filtering
[*]Nichtlinear Filtering
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[*]Image Decompositions
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[*]Multi-scale Representation
[*]Pyramids
[*]Filter Banks
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[*]Image Features
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[*]Structure
[*]Moments, Histograms
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Literature
References / Textbooks: Lecture slides, exercise sheets and matlab-code.
Further reading
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[*]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.
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Semester: Inverno 2022/23