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Multiple Descriptions Coinciding Lattice Vector Quantizer for Wavelet Image Coding

机译:小波图像编码的格向量量化器的多种描述

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Multiple description (MD) coding has been a popular choice for robust data transmission over the unreliable network channels. Lattice vector quantization provides lower computation for efficient data compression. In this paper, a new MD coinciding lattice vector quantizer (MDCLVQ) is presented. The design of the quantizer is based on coinciding 2-D hexagonal sublattices. The coinciding sublattices are geometrically similar sublattices, with the same index but generated by different generator matrices. A novel labeling algorithm based on the hexagonal coinciding sublattices is also developed. Performance results of the MDCLVQ scheme, together with the new labeling algorithm applied to standard test images, show improvements of the central and side decoders, as compared with the renowned techniques for several test images.
机译:多描述(MD)编码已成为在不可靠的网络通道上进行可靠数据传输的流行选择。格向量量化为有效的数据压缩提供了较低的计算量。本文提出了一种新的MD重合格向量量化器(MDCLVQ)。量化器的设计基于一致的二维六边形子格。一致的子格是几何上相似的子格,具有相同的索引,但由不同的生成器矩阵生成。还开发了一种基于六角形重合子格的新颖标记算法。 MDCLVQ方案的性能结果,加上应用于标准测试图像的新标记算法,与针对多个测试图像的著名技术相比,显示了中央和侧面解码器的改进。

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