| 基于混合神经网络的图像分类矢量量化方法 |
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| 引用本文： | 李万臣,王炼.基于混合神经网络的图像分类矢量量化方法[J].应用科技,2006,33(6):21-23. |
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| 作者姓名： | 李万臣 王炼 |
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| 作者单位： | 哈尔滨工程大学,信息与通信工程学院,黑龙江,哈尔滨,150001 |
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| 摘 要： | 介绍了一种基于自组织特征映射（SOFM）神经网络图像压缩的传统算法．通过对传统压缩算法的分析，提出了一种新的简单易行的分类矢量量化方法．新方法采用边缘检测，主元分析（PCA），自组织特征映射来设计码书，大大提高了图像的客观指标和主观视觉效果．实验表明，此方法效果明显优于传统的SOFM图像压缩算法．
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| 关 键 词： | 边缘检测 图像压缩 矢量量化 神经网络 |
| 文章编号： | 1009-671X（2006）06-0021-03 |
| 收稿时间： | 2005-10-20 |
| 修稿时间： | 2005年10月20 |
Image sorting vector quantization method based on mixed neural network |
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| LI Wan-chen,WANG Lian.Image sorting vector quantization method based on mixed neural network[J].Applied Science and Technology,2006,33(6):21-23. |
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| Authors: | LI Wan-chen WANG Lian |
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| Abstract: | A traditional algorithm of imge compression is proposed based on the neural network of SOFM. And a new and simple sorting vector quantization method is put forward by analyzing the traditional algorithm. The new method uses edge identification, PCA and SOFM to design the codebook, which greatly improves the objective index and the subjective visual impression. The simulation shows that the new method is better than the traditional SOFM image compression algorithm. |
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| Keywords: | edge identification image compression vector quantization neural network |
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