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A Fast Search Method for Vector Quantization Using Enhanced Sum Pyramid Data Structure

机译:基于增强和金字塔数据结构的矢量量化快速搜索方法

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Conventional vector quantization (VQ) encoding method by full search (FS) is very heavy computationally but it can reach the best PSNR. In order to speed up the encoding process, many fast search methods have been developed. Base on the concept of multi-resolutions, the FS equivalent fast search methods using mean-type pyramid data structure have been proposed already in [2]-[4]. In this Letter, an enhanced sum pyramid data structure is suggested to improve search efficiency further, which benefits from (1) exact computing in integer form, (2) one more 2-dimensional new resoludon and (3) an optimal pair selecting way for constructing the new resolution. Experimental results show that a lot of codewords can be rejected efficiently by using this added new resolution that features lower dimensions and earlier difference check order.
机译:通过全搜索(FS)进行的传统矢量量化(VQ)编码方法在计算上非常繁琐,但可以达到最佳的PSNR。为了加速编码过程,已经开发了许多快速搜索方法。基于多分辨率的概念,在[2]-[4]中已经提出了使用均值金字塔数据结构的FS等效快速搜索方法。在这封信中,提出了一种增强的和金字塔数据结构,以进一步提高搜索效率,这得益于(1)以整数形式进行精确计算,(2)一个新的二维新分辨率和(3)最佳的成对选择方式构建新的决议。实验结果表明,使用此新增加的分辨率较低的尺寸和较早的差异检查顺序,可以有效地拒绝许多代码字。

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