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一种新的基于Kohonen网络的图像矢量量化 被引量:1

A New Approach for Vector Quantization Based on Kohonen Neural Network
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摘要 矢量量化是一种重要的数据压缩方法.本文利用Kohonen自组织映射神经网络进行矢量量化,首次较为详细地讨论了具体实现的步骤与细节,并在此基础上为改善边缘质量,提出一种基于Laplas算子检测边缘弓引导神经网络训练的方法,并通过实验证明其效果是明显的. This paper extensively discusses the procedure for vector quantization based on Ko-honen self organizing feature map and uses a relative new version of frequency sensitive technology. The most important feature of it is to use a laplas operator to detect the image edge and induct the neural network to learn more information about the high frequency area in order to diminish block effects and therefore reconstruct the image with higher fidelity. The experiment results prove the effectiveness of this new approch.
出处 《系统工程与电子技术》 EI CSCD 1997年第3期55-57,68,共4页 Systems Engineering and Electronics
关键词 矢量量化编码 数据压缩 神经网络 信道编码 Vector quantization, Laplas operator, Neural network, LFKVQ
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  • 1胡兴堂,张兵,张霞,郑兰芬,童庆禧.基于小波变换的海量高光谱遥感数据分形编码压缩算法研究[J].中国科学(E辑),2006,36(B07):45-53. 被引量:3
  • 2MARCUS J,NADENAU J R,MURAT K. Color hnagc Compression: Exploiting Sensitivity Function [ J ]. IEEE Processing,2003,12( 1 ) :99 - 101. Wavelet-Based the Contrast . On Image.
  • 3CHANG Chip-Hong, RUI Xiao, THAMBIPILLAI S. A MSB Biased Self Organizing Feature Map for Still Color Image Compression [ D ]. Singapore: NanyangTechnological University ,2002.
  • 4DANDAWATE Y H, JOSHI M A, UMRANI S M. Performance Comparison of Color Image Compression Based on Enhanced Vector Quantizer Designed Using Different Color Spaces [ C ] //International Conference on Intelligent and Advanced System ,2007:64 - 65.
  • 5ZHAO Yu-li, LIANG Zhi, YU Hai. Fractal Color Image Coding Based on Isosceles Triangle Segmentation [ C ] // 2010 International Workshop on Chaos- Fractal Theory and Its Applications:54- 55.
  • 6孙宇佳,赵金辉,王远.分型图像压缩技术研究[J].科技信息(学术研究),2006(12):74-75.
  • 7黎洪松,许保华.一种用于视频对象编码的运动模式识别算法[J].电子学报,2007,35(12):2324-2328. 被引量:3
  • 8徐敬,付炜,胡彩宁,武华.基于小波图像编码算法的改进及实现[J].无线电通信技术,2008,34(5):62-64. 被引量:2
  • 9黄波,王煜坚.一种基于对象的可伸缩小波编码器[J].无线电通信技术,2009,35(1):35-38. 被引量:1

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