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Efficient cache-based spatial combinative lifting algorithm for wavelet transform

机译:基于高速缓存的小波变换空间组合提升算法

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Recently, a fast spatial combinative lifting algorithm (SCLA) for performing the wavelet transform (WT) was presented by Meng and Wang, and the SCLA speeds up the well-known lifting scheme presented by Daubechies and Sweldens. Employing the concept in the block-based WT by Bao and Kuo, this letter presents an efficient cache-based SCLA (CSCLA) for performing the WT. Theoretically, the number of total arithmetical operations required in the proposed CSCLA is equal to that in the SCLA. Experimental results confirm the computational advantage of our proposed CSCLA when compared to some other previous results. In addition, the VTune Performance Analyzer is used to evaluate the cache performance among the concerning algorithms. (C) 2004 Elsevier B.V. All rights reserved.
机译:最近,Meng和Wang提出了一种用于执行小波变换(WT)的快速空间组合提升算法(SCLA),该SCLA加快了Daubechies和Sweldens提出的众所周知的提升方案。这封信采用了Bao和Kuo的基于块的WT中的概念,提出了一种有效的基于WT的基于缓存的SCLA(CSCLA)。从理论上讲,建议的CSCLA中所需的总算术运算数等于SCLA中的算术运算数。与其他先前的结果相比,实验结果证实了我们提出的CSCLA的计算优势。此外,“ VTune性能分析器”用于评估相关算法中的缓存性能。 (C)2004 Elsevier B.V.保留所有权利。

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