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Recent developments in multidimensional multirate systems

机译:多维多速率系统的最新发展

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摘要

Multidimensional (MD) multirate systems, which find applications in the coding and compression of image and video data, have recently attracted much attention. The basic building blocks in an MD multirate system are the decimation matrix M, the expansion matrix L, and MD digital filters. With D denoting the number of dimensions, M and L are D×D nonsingular integer matrices. When these matrices are diagonal, most of the one-dimensional (1-D) multirate results can be extended automatically, using separable approaches (i.e., separable operations in each dimension). Separable approaches are commonly used in practice due to their low complexity in implementation. However, nonseparable operations, with respect to nondiagonal decimation and expansion matrices, often provide more flexibility and better performance. Several applications, such as the conversion between progressive and interlaced video signals, actually require the use of nonseparable operations. For the nonseparable case, extensions of 1-D results to the MD case are nontrivial. Some of these extensions, e.g., polyphase decomposition and maximally decimated perfect reconstruction systems, have already been successfully accomplished by some authors. However, there exist several 1-D results in multirate processing for which the MD extensions are even more difficult. In this paper, we will introduce some recent developments in these extensions. Some important results are: the design of nonseparable MD decimation / interpolation filters derived from 1-D filters, the generalized pseudocirculant property of alias-free maximally decimated filter banks, the commutativity of MD decimators and expanders, and applications in the efficient polyphase implementation of MD rational decimation systems. We will also introduce several other results of theoretical importance.
机译:多维(MD)多速率系统在图像和视频数据的编码和压缩中找到了应用,最近引起了很多关注。 MD多速率系统的基本构建模块是抽取矩阵M,扩展矩阵L和MD数字滤波器。用D表示维数,M和L是D×D非奇异整数矩阵。当这些矩阵是对角线时,可以使用可分离的方法(即每个维中的可分离的运算)自动扩展大多数一维(1-D)多速率结果。可分离的方法由于其实现的低复杂性而在实践中被普遍使用。但是,就非对角抽取和扩展矩阵而言,不可分割的操作通常会提供更大的灵活性和更好的性能。诸如逐行和隔行视频信号之间的转换之类的几种应用实际上需要使用不可分离的操作。对于不可分离的情况,将一维结果扩展到MD情况是不平凡的。其中一些扩展,例如多相分解和最大抽取的完美重构系统,已经被一些作者成功完成。但是,在多速率处理中存在多个一维结果,因此MD扩展甚至更加困难。在本文中,我们将介绍这些扩展的一些最新进展。一些重要的结果是:从一维滤波器派生的不可分离的MD抽取/插值滤波器的设计,无别名最大抽取滤波器组的广义伪循环特性,MD抽取器和扩展器的可交换性,以及在有效地实现多相抽取的应用MD合理抽取系统。我们还将介绍其他具有理论重要性的结果。

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