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

机译:蜂窝神经网络(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 Networkstructure 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 thegain of the output function may also improve some of the network capabilities.
机译:在本工作中,提出了一种将蜂窝神经网络(CNN)模型对灰度图像处理的改编。执行该任务编程网络以作为经典空间滤波器,利用神经网络结构以改善滤波效果。通过包含状态变量的反馈和基于图像的亮度来包括状态变量的反馈和每个神经元的输入偏置的改编来执行这种增强。正确选择输出功能也可以改善一些网络能力。

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