In order to improve the quality of Laplace operator image segmentation at a high real time capability this paper presented a synchronization dimensional structure filter for Laplace operator.
为了在继承拉普拉斯算子高实时性的前提下提高图像分割质量，设计了一个可与拉普拉斯算子差分计算同步进行滤波工作的空间滤波器。
PCNN model has similar group neurons synchronization release pulse characteristic, appropriate for the image segmentation.
PCNN模型具有相似群神经元同步发放脉冲的特性，适合于图像分割。
The introduction of the synchronization dimensional structure filter makes the Laplace operator improve the segmentation quality with a high real time capability by the original arithmetic.
同步空间滤波器的引入，可使原算法在低颜色阈值条件下获得高质量的图像分割结果，且该滤波器的行扫描数据录入方式可以保证高实时性。
The introduction of the synchronization dimensional structure filter makes the Laplace operator improve the segmentation quality with a high real time capability by the original arithmetic.
同步空间滤波器的引入，可使原算法在低颜色阈值条件下获得高质量的图像分割结果，且该滤波器的行扫描数据录入方式可以保证高实时性。
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