Proceedings PaperBenchmarks for 2D discrete wavelet transforms
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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.