A novel image de-noising algorithm combined PCNN with morphology

Zhang Hong-juan, Zhang Zong-nian, Lin Dong-mei, Ma Yi-de
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引用次数: 13

Abstract

After summarizing the characteristics of pulse noise, a novel de-noising algorithm combined pulse coupled neural network (PCNN) with mathematical morphology was proposed in this paper. Firstly, noisy points were located using the synchronous pulse burst property of PCNN, then, were processed using the morphological open-close filtering. Finally our algorithm was compared with median filtering, morphological open-close filtering and the algorithm combined PCNN with median filtering. The experimental results showed that the proposed algorithm performed well, which was at a cost of much more calculating time than median filtering and morphological filtering, and cost far less than the algorithm combined PCNN with median filtering.
一种将PCNN与形态学相结合的图像去噪算法
在总结脉冲噪声特征的基础上,提出了一种将脉冲耦合神经网络(PCNN)与数学形态学相结合的去噪算法。首先利用PCNN的同步脉冲突发特性定位噪声点,然后利用形态开闭滤波对噪声点进行处理。最后将该算法与中值滤波、形态开闭滤波以及PCNN与中值滤波相结合的算法进行了比较。实验结果表明,该算法性能良好,其计算时间远高于中值滤波和形态滤波,且成本远低于PCNN与中值滤波相结合的算法。
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