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Volume 24 Issue 5
May  2002
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Zhang Lei, Pan Quan, Zhang Hongcai, Dai Guanzhong . Signal compression by bitree-search-based wavelet transform[J]. Journal of Electronics & Information Technology, 2002, 24(5): 615-620.
Citation: Zhang Lei, Pan Quan, Zhang Hongcai, Dai Guanzhong . Signal compression by bitree-search-based wavelet transform[J]. Journal of Electronics & Information Technology, 2002, 24(5): 615-620.

Signal compression by bitree-search-based wavelet transform

  • Received Date: 2000-06-16
  • Rev Recd Date: 2001-09-26
  • Publish Date: 2002-05-19
  • ODWT (Orthogonal Discrete Wavelet Transform) is translation-variant, which will depress the compression efficiency. To avoid the deficiency, by holding all the even and odd indexed subsamples in every scale, a bitree structure is formed here. From any route of the bitree the signal can be reconstructed. According to sonic given criterion, a best transform route can be determined. The simulations show that the compression performance of the best transform route is better than that of the ordinary ODWT.
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  • I. Daubechies, Orthnomonal bases of compactly supported savelets, Comm. Pure. Appl. Math.,1988, 41(7), 909-996.[2]A. Cohen, I. Daubechies, J.-C. Feauvean, Biorthogonal bases of compactly supported wavelets,Comm. Pure. Appl. Math., 1992, 45(5), 485-560.[3]S. Mallat, A theory for multiresolution signal decomposition, The wavelet representation, IEEE Trans. on PAMI, 1989, PAMI-11(7), 674-693.[4]S. Mallat, Characterization of signals from multiscale edges, IEEE Trans. on PAMI, 1992, PAMI-14(7), 710-732.[5]S. Mallat, Singularity detection and processing with wavelet, IEEE Trans. on IT, 1992, IT-38(2),617-643.[6]J.M. Shapiro, Embedded image coding using zerostrees of wavelet coefficients, IEEE Trans. on SP, 1993, SP-41(12), 3445-3462.[7]R. Coifman, M. Wickerhauser, Entropy-based algorithms for best basis selection, IEEE Trans.on IT, 1992, IT-38(2), 713-718.[8]潘泉,张磊,子波域自适应滤波,航空学报,1997,18(5),583-586.[9]张磊,潘泉,一种子波域滤波算法的改进,电子学报,1999,27(2),19-21[10]Pan Quan, Zhang Lei, Two de-noising methods by wavelet transform, IEEE Trans. on SP, 1999,SP-47(12), 3401-3406.
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