SC²S Colloquium - September 28, 2016

Date:	September 28, 2016
Room:	02.07.023
Time:	3:00 pm, s.t.

Igor Shurmin: Efficient Implementation of The Whole-Genome Regression and Prediction Methods for Parallel Environments

TBA

Kevin Galim: Preconditioners for Tikhonov Regularization in Image Deblurring

In this thesis, new approaches for image deblurring are developed by combining Tikhonov regularization with preconditioning. The image blurring process can be expressed as ill posed linear equation with additive noise. To solve this type of equation and to reconstruct the original image, Tikhonov regularization is applied using a specific regularization matrix as input parameter. Typically, the identity matrix is chosen which, however, produces moderate results. A new attempt is to use preconditioners as regularization matrix, which are also used to solve ill posed problems. Matrices derived from the Incomplete LU factorization (ILU) preconditioner, the Sparse Approximate Inverse (SPAI) preconditioner and variations of these are tested in a simple image deblurring test where especially the inverse of the ILU preconditioner and a variation of the SPAI preconditioner yield superior results.