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Weyl-Heisenberg Transform Capabilities in JPEG Compression Standard

机译:Weyl-Heisenberg在JPEG压缩标准中的变换能力

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This paper is devoted to the development and research of a new compression technology based on Weyl-Heisenberg bases (WH-technology) for modifying the JPEG compression standard and improving its characteristics. For this purpose, the paper analyzes the main stages of the JPEG compression algorithm, notes its key features and problems that limit further enhancement of its efficiency. To overcome these limitations, it is proposed to use the real version of the two-dimensional discrete orthogonal Weyl-Heisenberg transform (DWHT) instead of the discrete cosine transform (DCT) at the stage of transformation coding. This transformation, unlike DCT, initially has a block structure and is built on the basis of the Weyl-Heisenberg optimal signal basis, the functions of which are orthogonal and well localized both in the frequency and time domains. This feature of DWHT allows for more efficient decorrelation and compression of element values in each block of the image after transformation coding. As a result, it is possible to obtain more efficient selection and screening of insignificant elements at the subsequent stages of quantization and information coding. Based on DWHT, a new version of the JPEG compression algorithm was developed, and convenient criteria for evaluating the compression efficiency and metrics of quality losses were proposed. The results of an experimental study are presented, confirming the higher compression efficiency of the proposed algorithm in comparison with the JPEG compression standard.
机译:本文致力于基于Weyl-Heisenberg基地(WH-Technology)的新型压缩技术的开发和研究,用于修改JPEG压缩标准,提高其特征。为此目的,本文分析了JPEG压缩算法的主要阶段,注意到其主要特征和问题限制了其效率的进一步提高。为了克服这些限制,建议在转换编码阶段使用二维离散正交Weyl-Heisenberg变换(DWHT)的实际版本而不是离散余弦变换(DCT)。与DCT不同,该转换最初具有块结构,并且基于Weyl-Heisenberg最佳信号的基础构建,其功能在频率和时域中是正交和良好的本地化。 DWHT的该特征允许在变换编码之后进行图像的每个块中的元素值更有效的去相关性和压缩。结果,可以在随后的量化和信息编码阶段获得更有效的选择和筛选微不足道的元素。基于DWHT,开发了新版本的JPEG压缩算法,提出了评估压缩效率和质量损失度量的方便标准。提出了一种实验研究的结果,与JPEG压缩标准相比,确认所提出的算法的更高压缩效率。

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