A Fast Algorithm for High Quality Vector Quantization Codebook Design
A Fast Algorithm for High Quality Vector Quantization Codebook Design
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DOI：
10.1007/3-540-60298-4_326
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发表时间：
1995-09
期刊：
影响因子：
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通讯作者：
C. Braccini;Fabio Cocurullo;F. Lavagetto
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文献类型：
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作者：
C. Braccini;Fabio Cocurullo;F. Lavagetto
在本文中，我们提出了一种解决最优矢量量化问题的新理论方法。事实上，我们的方法基于对簇间任意交换训练向量所引入的 MSE 失真影响的先验显式分析。即使使用对应于最简单可能情况的理论结果，所提出的算法在速度和性能上都远远优于 GLA 方法。对 USC 数据库不同图像的实验证明，该算法比 GLA 方法快 5 至 10 倍，收敛峰值信噪比 (PSNR) 提高高达 1.12 dB。
In this paper we present a new theoretical approach to the problem of optimal Vector Quantization. We base, in fact, our method on the a priori explicit analysis of the effects on the MSE distortion introduced by an arbitrary exchange of training vectors among clusters. Even when the theoretical results corresponding to the simplest possible case are used, the proposed algorithm outperforms the GLA method to an impressive extent both in speed and in performance. Experiments on different images from the USC database have proved that the proposed algorithm is 5 to 10 times faster than the GLA method increasing the convergence Peak Signal to Noise Ratio (PSNR) of up to 1.12 dB.