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Two-pass side-match finite-state vector quantization

机译:两遍边匹配有限状态矢量量化

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Abstract: Among the image coding techniques, vector quantization (VQ) has been considered to be an effective method for coding images at low bit rate. Side-match finite-state vector quantizer (SMVQ) exploits the correlations between the neighboring blocks (vectors) to avoid large gray level transition across block boundaries. In this paper, an improved SMVQ technique named two-pass side-match finite-state vector quantization (TPSMVQ) has been proposed. In TPSMVQ, the size of state codebook in the first pass is decided by the variances of neighboring blocks. In the second pass, we will improve the blocks encoded in the first pass whose variances are greater than a threshold. Moreover, not only the left and upper blocks but also the down and right blocks are used for constructing the state codebook. In our experiment results, the improvement of second pass is up to 1.5 dB in PSNR over the fist pass. In comparison to ordinary SMVQ, the improvement is upt to 1.54 dB at nearly the same bit rate.!17
机译:摘要:在图像编码技术中,矢量量化(VQ)被认为是一种以低比特率编码图像的有效方法。边匹配有限状态矢量量化器(SMVQ)利用相邻块(矢量)之间的相关性来避免跨块边界的大灰度级过渡。本文提出了一种改进的SMVQ技术,称为两遍边匹配有限状态矢量量化(TPSMVQ)。在TPSMVQ中,第一遍中状态码本的大小由相邻块的方差决定。在第二遍中,我们将改进在第一遍中编码的方差大于阈值的块。此外,不仅左块和上块,而且下块和右块都用于构造状态码本。在我们的实验结果中,与第一遍相比,第二遍的PSNR改善高达1.5 dB。与普通SMVQ相比,在几乎相同的比特率情况下,改善幅度高达1.54 dB!17

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