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一种全局优化的水平集图像分割方法

DOI: 10.11834/jig.20050106

Keywords: 图像分割算法,水平集方法,全局优化,符号距离函数,计算性能,灰度值,模型,源点,偏微分方程,邻域

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Abstract:

该文对Chan―Vese提出的水平集图像分割算法进行了改进,提出了分段光滑的Mumford―Shah全局优化的水平集图像分割模型,并对偏微分方程进行了修正,以提高模型的图像分割能力。实验表明,该方法不但解决了C―V方法对于灰度值渐进图像无法正确分割的问题,同时可更精确地描述原图像,是一种高效、稳定的图像分割模型。另外,针对水平集方法中符号距离函数构造计算量大的问题,还提出一种全邻域源点扫描法,以便通过对图像平面网格点的扫描来实现距离函数的快速计算,这种方法不仅计算性能稳定,而且速度快、精度高。

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