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中文摘要：
在Chan—Vese模型基础上，引入一个非凸的正则项，提出了一个新的变分水平集模型．一方面利用正则项的非凸性可起到更好的边缘保护作用，另一方面为水平集的演化增加了一个驱动力．同时，利用Nesterov算法实现了模型的快速求解．实验结果表明，与Chan—Vese模型相比，该模型在准确分割出图像目标的同时更好地刻画了边缘．
英文摘要：
A novel variational model based on the level set method is proposed. In the model, we introduce a nonconvex regularizer which performs better than the convex ones on protecting edges. On the other hand, the nonconvex regularizer is designed to provide a force which can help the evolution of the level set function. The Nesterov algorithm is introduced to implement the model. Experiments demonstrate the advantages of the proposed method over the Chan-Vese model in terms of both efficiency and accuracv.
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