Architecture for wavelet packet transform based on lifting steps
Parallel Computing - Parallel computing in image and video processing
Efficient cache-based spatial combinative lifting algorithm for wavelet transform
Signal Processing - Special section: New trends and findings in antenna array processing for radar
VLSI Architecture for Forward Discrete Wavelet Transform Based on B-spline Factorization
Journal of VLSI Signal Processing Systems
An efficient architecture for lifting-based two-dimensional discrete wavelet transforms
Integration, the VLSI Journal - Special issue: ACM great lakes symposium on VLSI
A Survey on Lifting-based Discrete Wavelet Transform Architectures
Journal of VLSI Signal Processing Systems
An efficient folded architecture for lifting-based discrete wavelet transform
IEEE Transactions on Circuits and Systems II: Express Briefs
An efficient architecture for lifting-based two-dimensional discrete wavelet transforms
Integration, the VLSI Journal - Special issue: ACM great lakes symposium on VLSI
The split-and-merge method in general purpose computation on GPUs
Parallel Computing
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In this paper, two new system architectures, overlap-state sequential and split-and-merge parallel, are proposed based on a novel boundary postprocessing technique for the computation of the discrete wavelet transform (DWT). The basic idea is to introduce multilevel partial computations for samples near data boundaries based on a finite state machine model of the DWT derived from the lifting scheme. The key observation is that these partially computed (lifted) results can also be stored back to their original locations and the transform can be continued anytime later as long as these partial computed results are preserved. It is shown that such an extension of the in-place calculation feature of the original lifting algorithm greatly helps to reduce the extra buffer and communication overheads, in sequential and parallel system implementations, respectively. Performance analysis and experimental results show that, for the Daubechies (see J.Fourier Anal. Appl., vol.4, no.3, p.247-69, 1998) (9,7) wavelet filters, using the proposed boundary postprocessing technique, the minimal required buffer size in the line-based sequential DWT algorithm is 40% less than the best available approach. In the parallel DWT algorithm we show 30% faster performance than existing approaches