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Wednesday, October 24, 2012

CSCAMM Seminar - Prof. Gitta Kutyniok - Image Inpainting and Sparse Approximation

One main problem in data processing is the reconstruction of missing data. In the situation of image data, this task is typically termed image inpainting. Recently, inspiring algorithms using sparse approximations and 1 minimization have been developed and have, for instance, been applied to seismic images. The main idea is to carefully select a representation system which sparsely approximates the governing features of the original image -- curvilinear structures in case of seismic data. The algorithm then computes an image, which coincides with the known part of the corrupted image, by minimizing the 1 norm of the representation coefficients. In this talk, we will develop a mathematical framework to analyze why these algorithms succeed and how accurate inpainting can be achieved. {Will appear in FYI on Oct 24, 2012
Start Time:
2:00 PM
End Time:
3:00 PM
Common Location Name:
Computer Science Instructional Center
Web Address:
Other Contact Information:
Ann Ekechukwu CSCAMM +1 301 405 0652

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