摘要
基于Hadamard变换和K-means理论,针对Chen的初始码书设计算法的随机性较强和峰值信噪比(PSNR)不高这两个缺点,提出了一种改进的码书设计算法。本算法利用统计特征量的分类平均法生成初始码书,然后提高求质心的频率,每当一个训练矢量被分类到胞腔时,就求出相应胞腔的质心来代替原有的码字。该算法结合LBG算法的优点,调整后的码字代表了整个胞腔的特性,加速了码书的收敛速度,提升了码书的性能。仿真实验结果表明,较Chen的算法图像效果,即峰值信噪比(PSNR),平均提高了0.5 dB,在迭代次数较小时甚至达0.9 dB。
This paper presents an improved codebook design algorithm of vector quantization which combines Hadamard-transform and K-means theory,according to the Chen＇s vector quantization algorithm which has two weaknesses of high randomness for the formation of initial codebook and low encoding quality（PSNR）.The proposed algorithm uses the statistical features of classification average method of training vectors to generate initial codebook,and then improves the frequency of calculation the cell＇s centroid.Whenever a training vector is classified into lumen,the corresponding cell＇s centroid will be calculated to instead of the original code word.The proposed algorithm combines the advantages of LBG algorithm.The adjusted code word represents the characteristics of the lumen,accelerates the convergence speed of codebook,and improves the performance of codebook.Compared with the Chen＇s algorithm,the encoding quality can be improved by 0.5 dB,even when the iteration is low,the PSNR is improved by 0.9 dB.
出处
《电信科学》
北大核心
2012年第2期82-85,共4页
Telecommunications Science
基金
重庆市科委自然科学基金资助项目(No.2020BB2407)
国家科技重大专项基金资助项目(No.2009ZX03001-004)
国家自然科学基金资助项目(No.61071116)
