Florian Knoll1, Yiqiu Dong2,
Christian Langkammer3, Michael Hintermller2,4, Rudolf
Stollberger1
1Institute of Medical Engineering, Graz
University of Technology, Graz, Austria; 2Institute of Mathematics
and Scientific Computing, University of Graz, Graz, Austria; 3Department
of Neurology, Medical University Graz, Graz, Austria; 4Department
of Mathematics, Humboldt-University of Berlin, Berlin, Germany
The
Total Variation regularization model is popular in MR research. In this
model, a regularization parameter controls the trade-off between noise
elimination, and preservation of image details. However, MR images are
comprised of multiple details. This indicates that different amounts of
regularization are desirable for regions with fine image details in order to
obtain better restoration results. This work introduces spatially dependent
regularization parameter selection for TV based image restoration. With this
technique, the regularization parameter is adapted automatically based on the
details in the images, which improves the reconstruction of details as well
as providing an adequate smoothing for the homogeneous parts.
Keywords