Efficient implementations of wavelet transforms have been derived, based on the FFT and short-length 'fast-running FIR algorithms'. However, for long one-dimensional arrays or two dimensional data, such as encountered in image processing, the time required to calculate wavelet transforms, even in the case of 'fast' FFT-based implementations, is still large. In order to reduce the time consumption of the wavelet transform and bring it closer to real-time implementation, this paper suggests the use of parallel processing based on the pipeline processor farm (PPF) methodology. The paper is mainly focussed on parallel implementation of the discrete wavelet transform (DWT), which is extensively used in image processing applications. The parallel environment in which the algorithms were implemented comprised two TMS320C40 boards with a total of six processors.
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