Hierarchical Mumford-Shah Model for Vector-valued Image Segmentation, Denoising and Reconstruction
多层Mumford-Shah向量值图像分割、去噪与重建模型

A novel hierarchical Mumford-Shah functional model is addressed to simultaneously segment, denoise and reconstruct the data within a given vector-valued image such as a color image, and to handle important image features such as triple points and other multiple junctions, which can be seen as a hierarchical case of the Mumford-Shah minimal partition problem for vector-valued images. At the same time, a new iterative tier-by-tier algorithm based on techniques of level set is proposed to minimize the functional, which is more effective and more simply than existing algorithms such as the hierarchical approach proposed by Tsai A et al. and the multiphase level set methods proposed by Chan T et al.