基于四叉树的可变速率定向平均形状增益矢量量化

R. Hamzaoui, Bertram Ganz, D. Saupe
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引用次数: 5

摘要

将平均形状增益矢量量化(MSGVQ)扩展到包括负增益和平方等距。平方等边和基于平均块强度的分类技术使我们能够在没有任何额外存储需求的情况下扩大MSGVQ码本大小,同时保持码本生成和编码可管理的复杂性。采用基于率失真准则的四叉树分割获得可变率码。实验结果表明,与以前的产品编码技术或基于四叉树的VQ方法相比,我们的方案具有更好的性能。
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Quadtree based variable rate oriented mean shape-gain vector quantization
Mean shape-gain vector quantization (MSGVQ) is extended to include negative gains and square isometries. Square isometries together with a classification technique based on average block intensities enable us to enlarge the MSGVQ codebook size without any additional storage requirements while keeping the complexity of both the codebook generation and the encoding manageable. Variable rate codes are obtained with a quadtree segmentation based on a rate-distortion criterion. Experimental results show that our scheme performs favorably when compared to previous product code techniques or quadtree based VQ methods.
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