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Side-Match Predictive Vector Quantization

机译:侧面匹配预测矢量量化

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摘要

Vector quantization (VQ) is widely used in low bit rate image compression. In this paper, two predictive vector quantization (PVQ) algorithms that combine the concept of side-match are proposed. By controlling the quantization distortion after encoding or searching the reconstructed vector with minimum side distortion before encoding, the two proposed algorithms can decrease the quantization distortion and computational complexity respectively. The bit rates are also reduced in both algorithms by using side-math technology. The performances of the proposed algorithms are compared with several previous VQ algorithms. Simulation results have shown the efficiency of the proposed algorithms.
机译:矢量量化(VQ)被广泛用于低比特率图像压缩中。本文提出了两种结合了侧面匹配概念的预测矢量量化(PVQ)算法。通过控制编码后的量化失真或在编码前以最小的边失真搜索重构矢量,这两种算法可以分别降低量化失真和计算复杂度。使用算术技术,两种算法中的比特率也都降低了。将所提出算法的性能与以前的几种VQ算法进行了比较。仿真结果表明了所提算法的有效性。

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