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Fast search algorithm for vector quantization using means and variances of code words

机译:利用码字均值和方差的矢量量化快速搜索算法

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Abstract: Vector Quantization has been applied to low-bit-rate speech and image compression. One of the most serious problems for vector quantization is the high computational complexity of searching for the closest codeword in the codebook design and encoding processes. To overcome this problem, a fast algorithm, under the assumption that the distortion is measured by the squared Euclidean distance, will be proposed to search for the closest codeword to an input vector. Using the means and variances of codewords, the algorithm can reject many codewords that are impossible to be candidates for the closest codeword to the input vector and hence save a great deal of computation time. Experimental results confirm the effectiveness of the proposed method.!22
机译:摘要:矢量量化已应用于低比特率语音和图像压缩。矢量量化最严重的问题之一是在码本设计和编码过程中搜索最接近的码字的高计算复杂性。为了克服该问题,将提出一种快速算法,该算法假设失真是通过平方的欧几里德距离来测量的,以寻找与输入向量最接近的码字。利用码字的均值和方差,该算法可以拒绝许多不可能成为最接近输入向量的码字的候选字的码字,从而节省了大量的计算时间。实验结果证实了该方法的有效性。22

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