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.
翻译:本文致力于开发和研究一种基于Weyl-Heisenberg基(WH技术)的新型压缩技术,用于改进JPEG压缩标准并提升其性能。为此,本文分析了JPEG压缩算法的主要阶段,指出了其关键特性以及限制其效率进一步提升的问题。为克服这些限制,建议在变换编码阶段使用二维离散正交Weyl-Heisenberg变换(DWHT)的实数版本替代离散余弦变换(DCT)。与DCT不同,该变换天然具有块结构,并基于Weyl-Heisenberg最优信号基构建,其函数在频域和时域均具有正交性和良好的局部化特性。DWHT的这一特点使得变换编码后图像每个块中的元素值能够实现更高效的去相关和压缩。因此,在后续的量化与信息编码阶段,可以更有效地筛选和剔除不重要的元素。基于DWHT,本文开发了JPEG压缩算法的新版本,并提出了评估压缩效率和量化质量损失的便捷标准。实验研究结果证实,所提算法相比标准JPEG压缩具有更高的压缩效率。