2022
DOI: 10.1007/s11227-022-04331-8
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An efficient implementation of one-dimensional discrete wavelet transform algorithms for GPU architectures

Abstract: In this paper, the authors present several self-developed implementation variants of the Discrete Wavelet Transform (DWT) computation algorithms and compare their execution times against the commonly approved ones for representative modern Graphics Processing Units (GPUs) architectures. The proposed solutions avoid the time-consuming modulo divisions and conditional instructions used for DWT filters wrapping by proper expansion of the DWTs input data vectors. The main goal of the research is to improve the com… Show more

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Cited by 7 publications
(1 citation statement)
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“…The continuous WT follows the shifting and scaling mechanism of the base signal, utilizing each conceivable wavelet, therefore, it is highly redundant. The discrete WT (which is applied in this study) on the other hand pursues only the limited set of wavelets such as locations and scales, thus, more efficiently [14]. The types of noises discussed earlier, i.e., baseline wanders and powerline interference can be constricted by applying the denoising technique based on discrete wavelet as performed in [15,16].…”
Section: Introductionmentioning
confidence: 99%
“…The continuous WT follows the shifting and scaling mechanism of the base signal, utilizing each conceivable wavelet, therefore, it is highly redundant. The discrete WT (which is applied in this study) on the other hand pursues only the limited set of wavelets such as locations and scales, thus, more efficiently [14]. The types of noises discussed earlier, i.e., baseline wanders and powerline interference can be constricted by applying the denoising technique based on discrete wavelet as performed in [15,16].…”
Section: Introductionmentioning
confidence: 99%