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Algorithms and architectures for 2D discrete wavelet transform

机译:二维离散小波变换的算法和架构

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摘要

The 2D Discrete Wavelet Transform (DWT) is an important function in many multimedia applications, such as JPEG2000 and MPEG-4 standards, digital watermarking, and content-based multimedia information retrieval systems. The 2D DWT is computationally intensive than other functions, for instance, in the JPEG2000 standard. Therefore, different architectures have been proposed to process 2D DWT. The goal of this paper is to review and to evaluate different algorithms and different kinds of architectures such as application-specific integrated circuits, field programmable gate array, digital signal processors, graphics processing units, and General-Purpose Processors (GPPs) that are used to process 2D DWT. In addition, we implement the 2D DWT using different algorithms on GPPs enhanced with multimedia extensions. The experimental results show that the largest speedup of the vectorized 2D DWT over the scalar implementation is about 2.8 for first level decomposition. Furthermore, the characteristics of the 2D DWT and disadvantages of the existing architectures such as GPPs enhanced with SIMD instructions are discussed.
机译:2D离散小波变换(DWT)是许多多媒体应用程序中的重要功能,例如JPEG2000和MPEG-4标准,数字水印和基于内容的多媒体信息检索系统。 2D DWT比其他功能(例如,JPEG2000标准)在计算上更加密集。因此,已经提出了不同的架构来处理2D DWT。本文的目的是审查和评估使用的不同算法和不同类型的体系结构,例如专用集成电路,现场可编程门阵列,数字信号处理器,图形处理单元和通用处理器(GPPs)处理2D DWT。此外,我们在多媒体扩展增强的GPP上使用不同的算法来实现2D DWT。实验结果表明,对于第一级分解,矢量化2D DWT在标量实现上的最大加速约为2.8。此外,还讨论了2D DWT的特性以及现有架构(例如用SIMD指令增强的GPP)的缺点。

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