一种用于图像编码的条件熵编码多级矢量量化器

X. Yuan, V. Ingle
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引用次数: 1

摘要

只提供摘要形式。提出了一种利用块间相关性的矢量量化(VQ)算法。尽管对于低比特率应用程序很有用,但是标准的表查找VQ有一个缺点,即存储和计算需求随着向量维度呈指数增长。在实践中,向量的大小通常从3*3到5*5。在这种大小下,我们发现相邻块之间仍然存在很强的相关性。实验表明,该方法的编码性能总体上优于先前设计的VQ码。到目前为止,各种数字图像编码的实验结果在30db ~ 36db范围内,约0.5 b.p.p。
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A conditional entropy-coded multi-stage vector quantizer for image coding
Summary form only given. A vector quantization (VQ) algorithm that utilizes this interblock correlation is proposed. Despite its usefulness for low bit-rate applications, the standard, table-lookup VQ has the drawback of exponential growth of both storage and computation requirements with vector dimension. In practice, the vector size is typically from 3*3 to 5*5. With this size, it has been found that there is still strong correlation between neighboring blocks. Experiments have shown that the approach generally gives better coding performance than previously designed VQ codes. So far, experimental results for coding various digital images are in the range of 30 dB to 36 dB with about 0.5 b.p.p.<>
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