结合脉冲耦合神经网络与模糊算法进行四值图像去噪

该文研究了如何将模糊算法用于脉冲耦合神经网络(Pulse Coupled Neural Network,PCNN),进行四值图像去噪,提出了基于模糊PCNN的图像去噪算法.计算机仿真结果表明,将模糊算法与PCNN相结合,可有效地去除被噪声污染的四值图像的噪声,且恢复图像的视觉效果明显地好于用另两种常用的图像去噪方法(中值滤波和均值滤波)得到的结果.在医用图像和军事图像处理方面,四值图像的去噪恢复是非常有价值的,故本文对于PCNN的理论研究和实际应用均有重要的意义。

Noise-Reducing of Fourlevel Image Using PCNN and Fuzzy Algorithm

This paper describes how to combine PCNN(Pulse Coupled Neural Network) with fuzzy algorithm to reduce the noise of four-level images. Meanwhile, the image noise-reducing algorithm based on the fuzzy PCNN is brought forward. The results of computer simulations show that noisy four-level images can be restored efficiently by using fuzzy PCNN and visual effects of restoration images by using fuzzy PCNN are much better than those by using two usual image noising-reducing methods, the median filter and the mean filter. Noise-reducing of the four-level images plays an important role in the medical image processing and the military image processing. Therefore, this paper contributes to both the theoretical researches on PCNN and the applications of PCNN.