采用分量均值正交分割法设计矢量量化初始码书

来源期刊:中南大学学报(自然科学版)2010年第2期

论文作者:邓宏贵 郭晟伟

文章页码:628 - 631

关键词:矢量量化;初始码书;分量均值;正交分割

Key words:vector quantization; initial codebook; component mean; orthogonal segmentation

摘    要:提出一种新的矢量量化初始码书设计算法即分量均值正交分割法。其原理是:利用分量均值对样本空间进行正交分割,使初始码字尽量散开,得到充分利用。研究结果表明:分量均值正交分割法在不同图像、不同码书下,与随机法相比,峰值信噪比提高1.0~1.3 dB,训练时间增加不超过30%;与分裂法相比,峰值信噪比相差小于0.1 dB,训练速度提高1.0~1.5倍;与其他算法相比,在量化失真和训练速度2个相互冲突的指标之间能取得更好的均衡。

Abstract: A new algorithm component mean orthogonal segmentation algorithm (CMOSA) was proposed to generate vector quantization initial codebook using component mean. The results show that in different images and different codebook sizes, compared with random algorithm, peak signal to noise ratio rises by 1.0-1.3 dB, and training time increases no more than 30%. Compared with splitting algorithm, peak signal to noise ratio difference is less than 0.1 dB, but the training speed improves 1.0-1.5 times. Between training speed and quantization distortion of the two conflicting indicators, CMOSA achieves a better balance than other algorithms.

基金信息:国家自然科学基金资助项目
国家高技术研究发展计划(“863”计划)子课题

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