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Applications of cellular neural networks (CNN) to grey scale image filtering

机译:细胞神经网络(CNN)在灰度图像滤波中的应用

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In the present work an adaptation of the cellular neural network (CNN) model to grey scale image processing is proposed. This task is performed programming the network to work as a classical spatial filter, taking advantage of the neural network structure in order to improve the filtering effects. This enhancement is carried out by the inclusion of the feedback of the state variables and the adaptation of the input bias of every neuron based on the brightness of the image. A proper choice of the gain of the output function may also improve some of the network capabilities.
机译:在本工作中,提出了一种适用于灰度图像处理的蜂窝神经网络(CNN)模型。通过利用神经网络结构来提高网络的过滤效率,对网络进行编程以使其作为经典的空间过滤器来执行此任务。这种增强是通过包含状态变量的反馈以及基于图像亮度对每个神经元的输入偏置进行调整来实现的。输出功能的增益的适当选择,也可以改善一些网络功能。

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