Image decomposition and staircase effect reduction based on total generalized variation
Total variation (TV) is widely applied in image processing. The assumption of TV is that an image consists of piecewise constants, however, it suffers from the so-called staircase effect. In order to reduce the staircase effect and preserve the edges when textures of image are extracted, a new image decomposition model is proposed in this paper. The proposed model is based on the total generalized variation method which involves and balances the higher order of the structure. We also derive a numerical algorithm based on a primal-dual formulation that can be effectively implemented. Numerical experiments show that the proposed method can achieve a better trade-off between noise removal and texture extraction, while avoiding the staircase effect efficiently.