Abstract
The classical first order Vese-Osher model is capable of decomposing an image into its structure and texture components. However, an undesirable feature of this model for the task is the ‘staircase’ side effect that appears in the structure component. In this paper, we propose a second order Vese-Osher model for image decomposition, which incorporates second order derivative information and is able to eliminate the side effect of the first order model. In order to avoid directly calculating the high order nonlinear partial differential equation (PDE) of the proposed model, the split Bregman algorithm is applied, which allows the use of fast Fourier transform and analytical generalized soft thresholding equation. Experiments are conducted to demonstrate the effectiveness and efficiency of the proposed model.
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