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基于二叉樹搜索的小波變換信號壓縮

張磊,  潘泉,  張洪才,  戴冠中

張磊, 潘泉, 張洪才, 戴冠中. 基于二叉樹搜索的小波變換信號壓縮[J]. 電子與信息學(xué)報(bào), 2002, 24(5): 615-620.
引用本文: 張磊, 潘泉, 張洪才, 戴冠中. 基于二叉樹搜索的小波變換信號壓縮[J]. 電子與信息學(xué)報(bào), 2002, 24(5): 615-620.
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.

基于二叉樹搜索的小波變換信號壓縮

Signal compression by bitree-search-based wavelet transform

  • 摘要: 正交離散小波變換由于缺乏平移不變性,會對信號壓縮的性能造成很大的影響。為避免這一缺陷,該文在每個(gè)變換尺度上均對偶采樣和奇采樣的結(jié)果進(jìn)行保留,產(chǎn)生一個(gè)三叉樹結(jié)構(gòu),由此二叉樹的任意一路徑均可重構(gòu)原信號,按照一定的準(zhǔn)則可以確定最優(yōu)分解路線。仿真結(jié)果表明,該變換方式較標(biāo)準(zhǔn)正交離散小波變換有更高的壓縮性能。
    Abstract: 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,張磊,子波域自適應(yīng)濾波,航空學(xué)報(bào),1997,18(5),583-586.[9]張磊,潘泉,一種子波域?yàn)V波算法的改進(jìn),電子學(xué)報(bào),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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出版歷程
  • 收稿日期:  2000-06-16
  • 修回日期:  2001-09-26
  • 刊出日期:  2002-05-19

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