Abstract
In this paper, we study to use nonlocal bounded variation (NLBV) techniques to decompose an image intensity into the illumination and reflectance components. By considering spatial smoothness of the illumination component and nonlocal total variation (NLTV) of the reflectance component in the decomposition framework, an energy functional is constructed. We establish the theoretical results of the space of NLBV functions such as lower semicontinuity, approximation and compactness. These essential properties of NLBV functions are important tools to show the existence of solution of the proposed energy functional. Experimental results on both grey-level and color images are shown to illustrate the usefulness of the nonlocal total variation image decomposition model, and demonstrate the performance of the proposed method is better than the other testing methods.
Original language | English |
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Pages (from-to) | 334-355 |
Number of pages | 22 |
Journal | Numerical Mathematics |
Volume | 7 |
Issue number | 3 |
DOIs | |
Publication status | Published - Aug 2014 |
Scopus Subject Areas
- Modelling and Simulation
- Control and Optimization
- Computational Mathematics
- Applied Mathematics
User-Defined Keywords
- Illumination
- Image decomposition
- Iterative method
- Nonlocal total variation
- Reflectance