Department of Mathematics

Inverse problems in image processing

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Organizers M. Plesinger and E. Kokiopoulou
ML H 34.3
Thu 15:00--17:00
First meeting 23. 9. 2010
Prerequisites Numerical Linear Algebra, Matrix Computations, MATLAB
This seminar focuses on the solution of image deblurring problems which belong to a broad class of so called inverse problems in image processing. Such problems arise, for example, in computer tomography (CT) when the true image data can not be obtained directly, but typically a smooth version of it is observed instead. In order to solve the inverse problem i.e., reconstruct the original (non-smooth) data from the smooth observation, one has to use regularization techniques, which impose certain regularity conditions on the reconstructed image data.
Literature Selected chapters from the following references:

[1]. Per Christian Hansen, James G. Nagy, and Dianne P. O'Leary: Deblurring Images, Matrices, Spectra and Filtering, SIAM, 2006.

[2]. Per Christian Hansen: Discrete Inverse Problems: Insight and Algorithms, SIAM, 2010.

MATLAB Useful MATLAB packages:

Per Christian Hansen: Regularization Tools Version 4.1 (for Matlab Version 7.3),

Per Christian Hansen, James G. Nagy, and Dianne P. O'Leary: HNO package,

Office hours Tuesday 14:00--15:00
Additional information The students are expected to:
  • regularly attend the seminar,
  • give a successful talk in English,
  • write a short report (summary) up to 3 pages,
  • optionally: implement in MATLAB some of the numerical experiments involved in their assignment.
Files to download A Short Introduction to Image Deblurring (slides)
Reading Assignments Topics
Optional MATLAB Task (Blurred testing images)
Timetable here

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