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基于Hopfield神经网络的图像矢量量化
引用本文:荣秋生,潘梅森,颜君彪. 基于Hopfield神经网络的图像矢量量化[J]. 微计算机信息, 2007, 23(6): 301-302
作者姓名:荣秋生  潘梅森  颜君彪
作者单位:415000,湖南常德,湖南文理学院计算机科学与技术系
基金项目:湖南省教育厅科研项目;湖南省教育厅资助项目
摘    要:矢量量化是图像压缩的重要方法。论文提出了基于Hopfield神经网络的图像矢量量化方法,该方法首先构造聚类表格;然后聚类表格按离散Hopfield神经网络串行方式运行;最后根据得到的最终码字集,对图像进行矢量量化。论文最后给出模拟实验和结果比较,结果表明该方法是有效的,生成的码本质量优于传统的LBG算法。

关 键 词:矢量量化  码本  LBG算法  Hopfield神经网络
文章编号:1008-0570(2007)02-3-0301-02
修稿时间:2006-01-03

A Method of Image Vector Quantization Based on Hopfield Neural Network
RONG QIUSHENG,PAN MEISEN,YANG JUNBIAO. A Method of Image Vector Quantization Based on Hopfield Neural Network[J]. Control & Automation, 2007, 23(6): 301-302
Authors:RONG QIUSHENG  PAN MEISEN  YANG JUNBIAO
Affiliation:RONG QIUSHENG PAN MEISEN YAN GJUNBIAO
Abstract:Image vector quantization is an important method in the image compression field. This paper proposed a method of image vector quantization based on hopfield Neural Network.This method first built a clustering form; then the clustering form worked according to the asynchronous mode of discrete hopfield neural network; Finally carried on the image vector quantization according to the final codebook set. The paper finally produced the experiments and the result comparison, the result indicated this method is effective and the codebook quality surpassed traditional the LBG algorithm.
Keywords:Vector Quantization  Codebook  LBG Algorithm  Hopfield Neural Nework1.
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