| TR#: | CIS-2011-03 |
| Class: | CIS |
| Title: | Fast Regularization of Matrix-Valued Images |
| Authors: | Guy Rosman, Yu Wang, Xue-Cheng Tai, Ron Kimmel and Alfred M. Bruckstein |
| CIS-2011-03.pdf | |
| Abstract: | Regularization of matrix-valued data is of importance in medical imaging, motion analysis and scene understanding. In this report we describe a novel method for efficient regularization of matrix group-valued images.
Using the augmented Lagrangian framework we separate the total-variation regularization of matrix-valued images into a regularization and projection steps, both of which are fast and parallelizable. We demonstrate the effectiveness of our method for denoising of several group-valued image types, with data in SO(n), SE(n), and SPD(n), and discuss its convergence properties. |
| Copyright | The above paper is copyright by the Technion, Author(s), or others. Please contact the author(s) for more information |
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