Notes on Performance of Bidiagonalization-Based Noise Level Estimator in Image Deblurring

0458347 - ÚI 2017 RIV SK eng C - Konferenční příspěvek (zahraniční konf.)
Hnětynková, Iveta - Kubínová, Marie - Plešinger, Martin
Notes on Performance of Bidiagonalization-Based Noise Level Estimator in Image Deblurring.
Algoritmy 2016. Bratislava: Slovak University of Technology, 2016 - (Handlovičová, A.; Ševčovič, D.), s. 333-342. ISBN 978-80-227-4544-4.
[ALGORITMY 2016. Conference on Scientific Computing /20./. Vysoké Tatry - Podbanské (SK), 13.03.2016-18.03.2016]
Grant CEP: GA ČR GA13-06684S
Institucionální podpora: RVO:67985807
Klíčová slova: image deblurring * linear ill-posed problem * noise * noise level estimate * Golub-Kahan iterative bidiagonalization
Kód oboru RIV: BA - Obecná matematika

Image deblurring represents one of important areas of image processing. When information about the amount of noise in the given blurred image is available, it can signifficantly improve the performance of image deblurring algorithms. The paper [11] introduced an iterative method for estimating the noise level in linear algebraic ill-posed problems contaminated by white noise. Here we study applicability of this approach to image deblurring problems with various types of blurring operators. White as well as data-correlated noise of various sizes is considered.
Trvalý link: http://hdl.handle.net/11104/0258613