基于学习向量量化的自组织映射图像编码中的动态位分配

38th Midwest Symposium on Circuits and Systems. Proceedings Pub Date : 1995-08-13 DOI:10.1109/MWSCAS.1995.510224

J. S. Neto, S.doN. Neto, Francisco Nascimento

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引用次数: 1

摘要

提出了一种用于自适应图像变换编码中动态位分配的自组织映射(SOM)神经网络。本文所显示的结果是针对输入层有30、96和128个神经元，竞争层有100个(10/spl倍/10)神经元的网络。使用学习向量量化LVQ1算法增强地图中的聚类。

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Dynamic bit allocation in image coding using a Self-Organizing Map with Learning Vector Quantization

A Self-Organizing Map (SOM) Neural Network for dynamic bit allocation in Adaptive Image Transform Coding is presented. The results shown in this paper are for nets with 30, 96 and 128 neurons in the input layer and 100 (10/spl times/10) neurons in the competition layer. The Learning Vector Quantization LVQ1 algorithm was used to enhance the clustering in the map.

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38th Midwest Symposium on Circuits and Systems. Proceedings

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