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Enhanced side match vector quantisation based on constructing complementary state codebook

机译:基于构造互补状态码本的增强侧匹配向量量化

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Side match vector quantisation (SMVQ) technique has been widely used in a lot of image compression and data hiding applications. It can effectively decrease the bit rate (BR) but the encoding visual quality of the image using SMVQ is generally poor because the correlation among neighbouring image blocks is still low. In this study, the authors propose a new enhanced SMVQ (ESMVQ) by introducing the concept of complementary state codebook (CSC) to improve the visual quality of SMVQ. Encoding input vectors by using CSC, ESMVQ can achieve almost the same encoding visual quality as using the conventional vector quantisation. As a result, the encoding visual quality of image can be significantly improved by exploiting the power of CSC. Experimental results show that the improvement of proposed ESMVQ method over SMVQ is up to 4.677 dB at a similar BR for image Lena when the main codebook size is 1024.
机译:侧面匹配矢量量化(SMVQ)技术已广泛用于许多图像压缩和数据隐藏应用程序中。它可以有效地降低比特率(BR),但由于相邻图像块之间的相关性仍然较低,因此使用SMVQ编码的图像的视觉质量通常较差。在这项研究中,作者通过引入互补状态码本(CSC)的概念来提高SMVQ的视觉质量,提出了一种新的增强型SMVQ(ESMVQ)。通过使用CSC编码输入向量,ESMVQ可以实现与使用常规向量量化几乎相同的编码视觉质量。结果,通过利用CSC的能力可以显着改善图像的编码视觉质量。实验结果表明,当主码本大小为1024时,在图像Lena的相似BR下,所提出的ESMVQ方法相对于SMVQ的改进高达4.677 dB。

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