Image segmentation via image decomposition and fuzzy region competition

• This paper presents a novel image segmentation method based on image decomposition.
• Our method simultaneously achieves image segmentation, decomposition and denoising.
• We design an optimal algorithm by dictionary learning and wavelet shrinkage.
• The proposed method improves the overall segmentation results.
• The proposed method has more strong robustness.

Taking into account the morphological diversity of images, this paper presents a novel multiphase image segmentation method that combines image decomposition and fuzzy region competition into a unified model. To efficiently solve the minimization of the energy functional, we design an optimal iteration algorithm which integrates a modified cartoon-texture dictionary learning algorithm and wavelet shrinkage. Compared with the classical fuzzy region competition method, the proposed method not only improves the overall segmentation results, but also has more strong robustness. A series of experimental results demonstrate the applicability and effectiveness of the proposed method.