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Bild-, Video- und mehrdimensionale Signalverarbeitung

Dozent/in

Details

Zeit/Ort n.V.:

  • Mo 12:15-13:45, Raum H9

Studienfächer / Studienrichtungen

  • WPF MT-MA-BDV ab Sem. 1
  • WPF CE-MA ab Sem. 1
  • WPF IuK-MA-ES-EEI ab Sem. 1
  • WPF IuK-MA-KN-EEI ab Sem. 1
  • WPF IuK-MA-MMS-EEI ab Sem. 1
  • WPF IuK-MA-REA-EEI ab Sem. 1
  • WF ICT-MA ab Sem. 1
  • WPF ICT-MA-NDC ab Sem. 1
  • WPF ICT-MA-MPS ab Sem. 1
  • WPF CME-MA ab Sem. 3
  • WF EEI-MA ab Sem. 1
  • WF WING-MA ab Sem. 1
  • WPF ASC-MA ab Sem. 1
  • WPF MT-MA-MEL ab Sem. 1

Prerequisites / Organizational information

Prerequisite: Lecture "Signals & Systems I+II"
At the first visit, access to the StudOn course has to be requested via the link https://www.studon.fau.de/studon/goto.php?target=crs_2002842 and will be granted by the course assistant.

Inhalt

Point operations
Histogram equalization, gamma correction

Binary operations
Morphological filters, erosion, dilation, opening, closing

Color spaces
Trichromacy, red-green-blue color spaces, color representation using hue, saturation and value of intensity

Multidimensional signals and systems
Theory of multidimensional signals and systems, impulse response, linear image filtering, power spectrum, Wiener filtering

Interpolation of image signals
Bi-linear interpolation, bi-cubic interpolation, spline interpolation

Image feature detection
Image features, edge detection, Hough transform, Harris corner detector, texture features, co-occurrence matrix

Scale space representation
Laplacian of Gaussian, difference of Gaussian, scale invariant feature transform, speeded-up robust feature transform

Image matching
Projective transforms, block matching, optical flow, feature-based matching using SIFT and SURF, random sample consensus algorithm

Image segmentation
Amplitude thresholding, k-means clustering, Bayes classification, region-based segmentation, combined segmentation and motion estimation, temporal segmentation of video

Transform domain image processing
Unitary transform, Karhunen-Loeve transform, separable transform, Haar and Hadamard transform, DFT, DCT

Empfohlene Literatur

J.-R. Ohm: |Multimedia Content Analysis|, Springer Verlag, 2016 J. W. Woods: |Multidimensional Signal, Image, and Video Processing and Coding|, Academic Press, 2. Auflage, 2012

ECTS-Informationen

Titel

Image, Video, and Multidimensional Signal Processing

Credits

5

Inhalt:

*Point operations*

Histogram equalization, gamma correction


*Binary operations*

Morphological filters, erosion, dilation, opening, closing


*Color spaces*

Trichromacy, red-green-blue color spaces, color representation using hue, saturation and value of intensity


*Multidimensional signals and systems*

Theory of multidimensional signals and systems, impulse response, linear image filtering, power spectrum, Wiener filtering


*Interpolation of image signals*

Bi-linear interpolation, bi-cubic interpolation, spline interpolation


*Image feature detection*

Image features, edge detection, Hough transform, Harris corner detector, texture features, co-occurrence matrix


*Scale space representation*

Laplacian of Gaussian, difference of Gaussian, scale invariant feature transform, speeded-up robust feature transform

*Image matching*

Projective transforms, block matching, optical flow, feature-based matching using SIFT and SURF, random sample consensus algorithm


*Image segmentation*

Amplitude thresholding, k-means clustering, Bayes classification, region-based segmentation, combined segmentation and motion estimation, temporal segmentation of video


*Transform domain image processing*

Unitary transform, Karhunen-Loeve transform, separable transform, Haar and Hadamard transform, DFT, DCT

Literature:

J.-R. Ohm: |Multimedia Content Analysis|, Springer, 2016 J. W. Woods: |Multidimensional Signal, Image, and Video Processing and Coding|, Academic Press, 2^nd^ edition, 2012

Zusätzliche Informationen

Erwartete Teilnehmerzahl: 50

www: https://www.studon.fau.de/studon/goto.php?target=crs_2002842