🤖 AI Summary
To address the blocking artifacts and insufficient frequency-domain localization inherent in JPEG’s discrete cosine transform (DCT), this paper proposes a novel image compression method based on the real two-dimensional discrete Weyl–Heisenberg transform (DWHT). For the first time, the Weyl–Heisenberg orthogonal basis—exhibiting joint time-frequency compact localization—is integrated into the JPEG framework as a drop-in replacement for DCT, preserving format compatibility while substantially improving energy compaction and decorrelation. The method incorporates adaptive quantization, optimized entropy coding, and newly designed metrics for compression efficiency evaluation and distortion measurement. Experimental results demonstrate that, at equivalent subjective quality, the proposed approach achieves an average PSNR gain of 1.2–2.8 dB over JPEG, with notably superior detail preservation at low bitrates (<0.5 bpp) and significantly enhanced compression efficiency.
📝 Abstract
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.