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- W2077172479 abstract "Shearlet representation has gained more prominence in recent year as a flexible mathematical framework which enables the efficient analysis of anisotropic phenomena by combining multiscale analysis with the ability to handle directional information. Based on this, we present a new variational model for image decomposition in shearlet smoothness spaces. The new model can be seen as generalizations of Daubechies -Teschke's model. By replacing the Besov regularization term by a shearlet-based regularization term, and writing the problem in a shearlet framework, we obtain elegant shearlet shrinkage schemes. The experiments on decomposition of images show that our algorithm is very efficient." @default.
- W2077172479 created "2016-06-24" @default.
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- W2077172479 date "2014-11-01" @default.
- W2077172479 modified "2023-09-23" @default.
- W2077172479 title "Variational Image Decomposition in Shearlet Smoothness Spaces" @default.
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- W2077172479 doi "https://doi.org/10.1109/cis.2014.25" @default.
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