基于视觉信息的PCNN参数自适应设定及模型改进

Adaptive Parameters Settings Method of PCNN Based on Visual Information and its Modified Model

脉冲耦合神经网络(PCNN)参数决定该模型在数字图像处理领域的应用。现阶段网络参数自适应设定是依据图像统计信息或网络自身结构。基于此,提出基于生物视觉信息的PCNN参数自适应设置方法及模型改进。该方法通过对生物视觉感知理论与PCNN网络性质的分析,揭示了视觉感知理论与PCNN网络参数M、W和β的同源性,给出依据视觉感知模型自适应设定PCNN网络参数W、M和β的方法,并设计出具有生物视觉特征的PCNN改进模型。实验验证了该模型的几何不变性,在基于内容的图像检索领域取得了良好效果。

The parameters of pulse dual neural network （PCNN） determine the application of the model in the field of digital image processing. But adaptive settings of network parameters are based on the information of image statistics or network structure. Based on this, the adaptive parameters settings method of PCNN based on visual information was proposed and model was improved. By analyzing the nature of the biological visual perception theory and PCNN net- work, the method reveals the homology of the theory of visual perception and PCNN network parameters M,W and/~ The M,W and/？ of adaptive parameter setting method were given on the basis of visual perception model. The PCNN improvement model of Biological visual features was designed. The experiments verify the geometric invarianee of the model. And it is proved that the model achieves good results at the field of Content-based image retrieval.