The lifting structure has been shown to be computationally efficient for implementing filter banks. The hardware implementation of a filter bank requires that the lifting coefficients be quantized. The quantization method determines compression performance, hardware size, hardware speed and energy. We investigate the implementation of two lifting coefficient sets, rational and irrational, for the biorthogonal 9/7 wavelet. Six different approaches are used to find optimal quantized lifting coefficients from these sets. We find that the best hardware and PSNR performance is obtained using the rational coefficient set quantized with gain compensation and lumped scaling.
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