LBG算法，矢量量化。Linde，Buzo和Gray于1980年提出LBG算法，又称为K-means算法。该算法是基于最近邻原则把训练矢量分配到与它欧式距离最小的码字的簇中。

矢量量化VQ，是一个常见的压缩技术。Linde, Buzo, and Gray (LBG)提出了基于训练序列的Vector Quantization (VQ)算法。

Linde, Buzo, and Gray (LBG) proposed a VQ design algorithm based on a training sequence. The use of a training sequence bypasses the need for multi-dimensional integration. The LBG algorithm is of iterative type and in each iteration a large set of vectors, generally referred to as training set, is needed to be processed. Usually, vectors sampled from a group of typical signals to be encoded altogether construct a training set T={x1,x 2,?.x M} ,where xi represents a sampled training vector and M represents the size of training set which is far greater than the codebook size N.

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Linde, Buzo, and Gray (LBG) proposed a VQ design algorithm based on a training sequence. The use of a training sequence bypasses the need for multi-dimensional integration. The LBG algorithm is of iterative type and in each iteration a large set of vectors, generally referred to as training set, is needed to be processed. Usually, vectors sampled from a group of typical signals to be encoded altogether construct a training set T={x1,x 2,?.x M} ,where xi represents a sampled training vector and M represents the size of training set which is far greater than the codebook size N.

利用matlab实现采用LBG算法实现语音信号的矢量量化程序

LBG算法码书设计,数字图像处理课程设计实现图像增强的码书算法设计。

平台vs c++与opencv 实现图像压缩 训练矢量 LBG算法设计码书 根据码书显示压缩后图像