Abstract
A preliminary structure + texture image decomposition is very useful for a number of digital image processing tasks, as different strategies are supposed to be employed for processing the structure and texture image components. In this paper, a new variational structure + texture image decomposition method is developed. The main ingredients of the proposed approach are: (1) using a low-pass filtered level-set curvature of the input image as a guidance image; (2) texture suppressing by minimizing a variable exponent energy, where the variable exponent is learned from the result of the curvature-guided image filtering. Numerical experiments demonstrate that the method is competitive with the current state of the art in structure + texture image decomposition. Several applications are considered.
Original language | English |
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Pages (from-to) | 5192-5203 |
Number of pages | 12 |
Journal | IEEE Transactions on Image Processing |
Volume | 27 |
Issue number | 10 |
Early online date | 4 Jul 2018 |
DOIs | |
Publication status | Published - Oct 2018 |
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Alexander Belyaev
- School of Engineering & Physical Sciences - Associate Professor
- School of Engineering & Physical Sciences, Institute of Sensors, Signals & Systems - Associate Professor
Person: Academic (Research & Teaching)