基于简化Mumford-Shah模型的水平集图像分割算法

为解决传统图像分割方法受噪声和边界轮廓影响而使分割效果不佳问题，基于简化的Mumford Shah模型的水平集图像分割算法通过将曲线嵌入水平集函数，利用函数的求解以达到曲线演化和图像分割的目的。试验表明此分割算法与初始轮廓线位置无关、不受边界轮廓线连续性限制、对图像噪声具有很强的鲁棒性，对均质灰度目标分割效果良好。

Level set image segmentation based on simple Mumford-Shah model

To overcome the deficiency of conventional methods in image segmentation influenced by image noise and edge contour,a level set approach to image segmentation was proposed on the basis of simplified Mumford-Shah model.Initial curve was embedded in the level set function,and image segmentation and curve evolution were accomplished when the function's solution was obtained.The experimental results show that it is a robust approach to image segmentation with noise,irrespective of edge continuous information and the curve initial position.Satisfactory effect has been achieved on image segmentation,especially homogeneous grayscale images.