Taking into account different feature components of images this paper presents a multiregion image segmentation model and algorithm based on image decomposition.Firstly

we introduce image decomposition term into the proposed image segmentation model.Image decomposition term can reduce the influence of texture and noise on our segmentation tasks.Secondly

we use sparsity regularization method to protect the edges and shape of the segmented regions.Finally

based on the augmented Lagrange multiplier method

we present an iterative wavelet shrinkage image segmentation algorithm which is guided by a diffusion flow.A series of experimental results show that the proposed method has strong anti-interference ability and it is more robust to noise.The proposed method can segment not only images with simple construction but also complex texture images.