Analogue weighted median filter based on cellular neural network for standard video signal processing

Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications Pub Date : 2002-07-22 DOI:10.1109/CNNA.2002.1035106

J. Kowalski

引用次数: 4

Abstract

A VLSI implementation of an analogue weighted median filter based on Cellular Neural Network (CNN) paradigm for standard video signal processing is described in this paper. This filter consists of feedforward nonlinear template B operating within the window of 3 by 3 pixels around the central pixel being filtered. The feedforward nonlinear coefficients are realized using a programmable nonlinear coupler circuits. Basic weighted median filter blocks and chip layout are presented. Technology applied for this implementation is CMOS AMS 0.8/spl mu/m CYE.

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基于细胞神经网络的模拟加权中值滤波用于标准视频信号处理

本文描述了一种基于细胞神经网络(CNN)范式的模拟加权中值滤波器的VLSI实现，用于标准视频信号处理。该滤波器由前馈非线性模板B组成，该模板B在被滤波的中心像素周围3 × 3像素的窗口内工作。采用可编程非线性耦合器电路实现前馈非线性系数。给出了基本加权中值滤波块和芯片布局。本实现采用的技术是CMOS AMS 0.8/spl mu/m CYE。

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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Proceedings of the 2002 7th IEEE International Workshop on Cellular Neural Networks and Their Applications

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