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An efficient codebook post-processing technique and a window-basedfast-search algorithm for image vector quantization

机译:一种有效的码本后处理技术和基于窗口的图像矢量量化快速搜索算法

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摘要

Vector quantization is an efficient image-coding technique to achieve a very low bit-rate compression. Furthermore, a lower bit rate can be achieved by equipping the vector quantizer with a memory unit or feedback loop so as to utilize the inter-vector correlation. For example, predictive vector quantization exploits the linear inter-vector correlation in the spatial domain by a linear vector prediction. Despite the better performance of this kind of vector quantizer, they are usually much more complex. In this paper, we proposed a simple but efficient codebook post-processing technique which enables the vector quantizer to possess a higher correlation preservation property. As is shown, the proposed post-processing technique leads to much higher inter-index correlation, of equivalently, smaller first-order (or higher order) entropy. Based on the special pattern of the codebook imposed by the post-processing technique, a window-based fast search (WBFS) algorithm is proposed. The WBFS algorithm not only accelerates the vector quantization processing, but also results in better rate-distortion performance
机译:矢量量化是一种有效的图像编码技术,可实现非常低的比特率压缩。此外,通过为矢量量化器配备存储单元或反馈回路,从而利用矢量间相关性,可以获得较低的比特率。例如,预测矢量量化通过线性矢量预测来利用空间域中的线性矢量间相关性。尽管这种矢量量化器的性能更好,但它们通常要复杂得多。在本文中,我们提出了一种简单而有效的码本后处理技术,该技术可使矢量量化器具有更高的相关性保留特性。如图所示,提出的后处理技术导致更高的索引间相关性,等效地,具有较小的一阶(或更高阶)熵。基于后处理技术对码本的特殊影响,提出了一种基于窗口的快速搜索(WBFS)算法。 WBFS算法不仅加速了矢量量化处理,而且还带来了更好的速率失真性能

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