Vector quantization(VQ) is always more powerful than scalar quantization in theory.
在理论上上矢量量化的性能总是优于标量量化。
参考来源 - 基于小波变换和误差竞争学习的矢量量化方法研究Multiple description image coding Arithmetic based on scalar quantization (MDSQ) can effectively improve the data receival quality.
标量量化多描述编码（MDSQ）算法能有效提高信息的传输接收效果。
参考来源 - 图像多描述编码的MDSQ算法及其Matlab实现—《电脑知识与技术》—2007年第24期—龙源期刊网·2,447,543篇论文数据，部分数据来源于NoteExpress
Vector quantization (VQ) is always more powerful than scalar quantization in theory.
在理论上上矢量量化的性能总是优于标量量化。
DCT coefficients were quantized through nonlinear scalar quantization and entropy coding.
变换系数采用非均匀标量量化和熵编码。
This paper combines multiple description scalar quantization and SPIHT coding to get efficient multiple description image coding over wireless error-prone network.
将多描述标量量化与SPIHT编码联合起来，得到无线差错网络环境下的高效多描述图像编码。
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