A block adaptive Bayesian wavelet shrinkage is proposed in this paper to accommodate the reduction of a kind of two-dimensionally, signal amplitude-related contamination, which is taken place in some military and biomedical applications. Wavelet shrinkage conventionally works under the assumption of signal-independent, additive Gaussian noise. For the temporally Gaussian but spatially signal amplitude-related noise, its denoising efficiency is depressed. To make use of the merit of wavelet denoising, the signal space is split to blocks and then wavelet shrinkage is conducted in each block, in which the signal amplitude is assumed to vary little. Results from simulation show that the proposed method outperforms the traditional one in signal-to-noise ratio improvement.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Block Adaptive Bayesian Wavelet Shrinkage for 2D Signal De-noising


    Contributors:
    Zhang, Dachun (author) / Liu, Gang (author) / Li, Hongbin (author) / Chu, Deqiang (author) / Kang, Yuebin (author)


    Publication date :

    2008-05-01


    Size :

    421531 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Wavelet de-noising for IMU alignment

    El-Sheimy, N. / Nassar, S. / Noureldin, A. | IEEE | 2004


    Wavelet De-Noising for IMU Alignment

    El-Sheimy, N. | Online Contents | 2004



    De-noising Method Research on RF Signal by Combining Wavelet Transform and SVD

    Li, Junyao / Li, Yongbin / Wang, Xiaoqiang et al. | Springer Verlag | 2017


    De-noising Method Research on RF Signal by Combining Wavelet Transform and SVD

    Li, Junyao / Li, Yongbin / Wang, Xiaoqiang et al. | British Library Conference Proceedings | 2018