• DocumentCode
    2081455
  • Title

    A novel inter-scale correlation image denoising method based on Dual-tree M-band wavelet

  • Author

    Yan, Jingwen ; Yang, Guide ; Zhang, Anfa

  • Author_Institution
    Inst. of Technol., Shantou Univ., Shantou, China
  • Volume
    1
  • fYear
    2008
  • fDate
    17-19 Nov. 2008
  • Firstpage
    131
  • Lastpage
    136
  • Abstract
    A novel inter-scale correlation image denoising method based on dual-tree M-band wavelet (DTT) is proposed in this paper. Dual-tree M-band wavelet transform is a shift-invariant, multi-scale and multi-direction transform based on a Hilbert pair of wavelets initially proposed by N. Kingsbury. Improving upon Xu¿s denosing algorithm based on wavelet inter-scale correlation, a new correlation modeling is provided between each high frequency detail subimage and corresponding M subimages in adjacent lower frequency scale. In the new algorithm, signal and noise are distinguished by the strength of the correlation, and combined with threshold functions. The experiment result shows that comparing with the classical denoising methods, for example, wavelet denoising method, Dual-tree complex wavelet denoising method, contourlet denoising method and so on..., the proposed denoising method achieves an excellent balance between suppressing noise effectively and preserving as many image details and edges as possible.
  • Keywords
    Hilbert transforms; correlation methods; image denoising; trees (mathematics); wavelet transforms; Hilbert pair; dual-tree M-band wavelet; inter-scale correlation image denoising; multi-direction transform; multi-scale transform; shift-invariant transform; wavelet denoising; Discrete transforms; Discrete wavelet transforms; Frequency; Image denoising; Image edge detection; Intelligent systems; Knowledge engineering; Noise reduction; Signal processing; Wavelet transforms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent System and Knowledge Engineering, 2008. ISKE 2008. 3rd International Conference on
  • Conference_Location
    Xiamen
  • Print_ISBN
    978-1-4244-2196-1
  • Electronic_ISBN
    978-1-4244-2197-8
  • Type

    conf

  • DOI
    10.1109/ISKE.2008.4730912
  • Filename
    4730912