Paper
22 March 1999 Benchmarks for 2D discrete wavelet transforms
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Abstract
Wavelet transform can be computed in the time domain by direct, polyphase, or run-length methods. Alternatively FFT methods can be used. Typical comparison of the computational effort in the literature are based on the number of float multiplications or float multiplication and additions. The break even point of the time and FFT methods are computed based on this counting. But todays computer architecture are to complex (e.g. pipelining, cache and CPU register utilization) to archive precise results by counting. Benchmarks are reported in this paper to compare different methods. In addition MMX code will be shown to give essential speed-ups. The benchmarks are conducted in connection with the ESA-MAE image compression algorithm.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Uwe Meyer-Baese "Benchmarks for 2D discrete wavelet transforms", Proc. SPIE 3723, Wavelet Applications VI, (22 March 1999); https://doi.org/10.1117/12.342938
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Discrete wavelet transforms

Image compression

Convolution

Wavelets

Algorithm development

Image processing

Optical filters

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