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Two-pass side-match finite-state vector quantization

机译:双通侧匹配有限状态矢量量化

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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.
机译:在图像编码技术中,矢量量化(VQ)被认为是以低比特率编码图像的有效方法。侧匹配的有限状态矢量量化器(SMVQ)利用相邻块(矢量)之间的相关性,以避免跨块边界的大灰度转换。在本文中,已经提出了一种名为双通侧匹配有限状态矢量量化(TPSMVQ)的改进的SMVQ技术。在TPSMVQ中,第一次传递中的状态码本的大小由相邻块的差异决定。在第二次通过中,我们将改善在第一次通过的差异大于阈值的第一传递中的块。此外,不仅左侧和上部块,而且还用于构建状态码本的左侧和右块。在我们的实验结果中,在拳头通过的PSNR中的改善高达1.5 dB。与普通的SMVQ相比,改善以几乎相同的比特率升高至1.54dB。

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