A hybrid method realizing shock filter by Cellular Neural Network

Pham Duc Long, P. T. Cat
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Abstract

Shock filter is an important type of the filters in image processing. In recent years, research on shock filters has been an interested topic in signal and image processing. In this paper we propose a method to realize the shock filter by CNN (Cellular Neural Network). The method offers fast processing time in comparison with that on the serial digital computers and can be used in many real-time image processing systems. We focus on development of the shock filter algorithm realizing edge enhancement and de-noising on the Bi-I CNN visual computer. Besides presenting the algorithm, many experiments on Bi-I are given for demonstration.
用细胞神经网络实现冲击滤波的混合方法
冲击滤波器是图像处理中滤波器的一种重要类型。近年来,冲击滤波器的研究一直是信号与图像处理领域的研究热点。本文提出了一种利用细胞神经网络(CNN)实现冲击滤波器的方法。与串行数字计算机相比,该方法具有更快的处理时间,可用于许多实时图像处理系统。重点研究了在Bi-I CNN视觉计算机上实现边缘增强和去噪的冲击滤波算法。除了介绍算法外,还在Bi-I上进行了大量实验验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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