基于脉冲耦合神经网络和形态学的改进去噪算法

通过总结脉冲噪声的特点和脉冲耦合神经网络以及数学形态学去噪的工作方式，提出了一种基于脉冲耦合神经网络模型和形态学的改进的脉冲噪声去除算法，该算法在一定程度上降低了在恢复图像的过程中噪声之间的相互干扰。实验结果表明，文章提出的改进算法的实验效果要明显优于申值滤波和数学形态学滤波算法，也要优于基本的基于脉冲耦合神经网络和形态学相结合的去噪算法。

An Improved Pulse Noise Removing Algorithm Based on PCNN and Morphology

After summarizing the characteristics of impulse noise and the way that Pulse Coupled Neural Networks and Morphological denoising algorithm work, An Improved Pulse Noise Removing Algorithm based on pulse coupled neural networks and morphology is proposed. This algorithm reduces the affect between the noises in the process of removing these noises. The experimental results show that the results of improved algorithm proposed in this paper is better than median and Mathematical Morphology algorithms obviously...