脉冲耦合神经网络模型参数估计及其图像分割

利用小波分析对图像进行多层分解,然后,用分解的低频系数重构图像作为模型链接权参数W的估计,再用一种最佳阈值方法估计阈值θ,最后用最大相关准则确定网络计算的迭代次数N,成功实现了图像的自动分割.实验仿真表明,该方法在模型参数自动估计的基础上避免了PCNN对图像的过平滑作用,分割图像保留了良好的轮廓和更多的细节.

Pulse coupled neural network model parameter estimationand image segmentation

In this paper,the wavelet analysis was applied to multi-layer decomposition of image.Then, it was linked to the right as a model parameter estimates of W with decomposition of the low-frequency coefficients of the reconstructed image.It was estimated an optimal threshold value of the threshold θ.The final maximum correlation criterion was used to determine network iteration times N.A successful automatic image segmentation was obtained.Experimental results showed that the method automatically estimated model parameters based on PCNN image to avoid over-smoothing effect,segmentation images retained a good profile and more details.