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Vector quantization with zerotree significance map for wavelet image coding

机译:小波图像编码的零树有效图矢量量化

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Variable-rate tree-structured vector quantization is applied to the coefficients obtained from an orthogonal wavelet decomposition. The set of vectors from different levels of the decomposition that correspond to the same orientation and spatial location are examined in various "zerotree" groups to determine the different bit rates and distortions achievable for the set. The decision not to code certain groups of vectors is based upon choosing the desired distortion/rate tradeoff from among the possibilities. Side information is sent to the decoder to inform it of the sequence of decisions. The resulting bit stream is entropy coded. Results of this method on the test image "Lena" yielded a PSNR of 30.16 dB at 0.148 bpp.
机译:可变速率树状结构矢量量化应用于从正交小波分解获得的系数。在各种“零树”组中检查对应于相同方向和空间位置的,来自不同分解级别的向量集,以确定该集合可实现的不同比特率和失真。不对某些矢量组进行编码的决定是基于从各种可能性中选择所需的失真/速率折衷。辅助信息被发送到解码器,以告知其决策顺序。产生的比特流被熵编码。该方法在测试图像“ Lena”上的结果在0.148 bpp处产生30.16 dB的PSNR。

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