A novel encoding algorithm for vector quantization using transformed codebook
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摘要
In this paper, a novel encoding algorithm for vector quantization is presented. Our method uses a set of transformed codewords and partial distortion rejection to determine the reproduction vector of an input vector. Experimental results show that our algorithm is superior to other methods in terms of the computing time and number of distance calculations. Compared with available approaches, our method can reduce the computing time and number of distance calculations significantly. Compared with the available best method of reducing the number of distance computations, our approach can reduce the number of distance calculations by 32.3–67.1%. Compared with the best encoding algorithm for vector quantization, our method can also further reduce the computing time by 19.7–23.9%. The performance of our method is better when a larger codebook is used and is weakly correlated to codebook size.
论文关键词:Nearest neighbors,KLT,Fast search algorithm,Vector quantization
论文评审过程:Received 2 July 2008, Revised 25 November 2008, Accepted 1 February 2009, Available online 10 February 2009.
论文官网地址:https://doi.org/10.1016/j.patcog.2009.02.001