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A Multiparametric Class of Low-complexity Transforms for Image and Video Coding
arXiv - CS - Multimedia Pub Date : 2020-06-19 , DOI: arxiv-2006.11418
D. R. Canterle, T. L. T. da Silveira, F. M. Bayer, R. J. Cintra

Discrete transforms play an important role in many signal processing applications, and low-complexity alternatives for classical transforms became popular in recent years. Particularly, the discrete cosine transform (DCT) has proven to be convenient for data compression, being employed in well-known image and video coding standards such as JPEG, H.264, and the recent high efficiency video coding (HEVC). In this paper, we introduce a new class of low-complexity 8-point DCT approximations based on a series of works published by Bouguezel, Ahmed and Swamy. Also, a multiparametric fast algorithm that encompasses both known and novel transforms is derived. We select the best-performing DCT approximations after solving a multicriteria optimization problem, and submit them to a scaling method for obtaining larger size transforms. We assess these DCT approximations in both JPEG-like image compression and video coding experiments. We show that the optimal DCT approximations present compelling results in terms of coding efficiency and image quality metrics, and require only few addition or bit-shifting operations, being suitable for low-complexity and low-power systems.

中文翻译:

用于图像和视频编码的低复杂度变换的多参数类

离散变换在许多信号处理应用中发挥着重要作用,近年来经典变换的低复杂度替代方案变得流行。特别是,离散余弦变换 (DCT) 已被证明便于数据压缩,被用于众所周知的图像和视频编码标准,例如 JPEG、H.264 和最近的高效视频编码 (HEVC)。在本文中,我们基于 Bouguezel、Ahmed 和 Swamy 发表的一系列作品介绍了一类新的低复杂度 8 点 DCT 近似。此外,还导出了一种包含已知变换和新颖变换的多参数快速算法。我们在解决多准则优化问题后选择性能最佳的 DCT 近似,并将它们提交给缩放方法以获得更大尺寸的变换。我们在类似 JPEG 的图像压缩和视频编码实验中评估这些 DCT 近似值。我们表明,最佳 DCT 近似在编码效率和图像质量指标方面呈现出令人信服的结果,并且只需要很少的加法或位移操作,适用于低复杂性和低功耗系统。
更新日期:2020-06-23
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