Signal processing using over-complete representations has been an active research field in recent years. In this article, we study the following two related problems: (1) given two wavelets and the Gaussian observation model, what is the optimal estimate of the signal which is corrupted by additive noise? and (2) to minimize the variance of the estimate, what is the relationship between the phase responses of the two scaling filters? Based on a study of these two problems, we develop a denoising algorithm. We test the proposed algorithm in image denoising and show that its performance is comparable to that of the state-of-the-art.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Signal estimation using multiple-wavelet representations and Gaussian models


    Beteiligte:
    Guang Deng, (Autor:in)


    Erscheinungsdatum :

    01.01.2005


    Format / Umfang :

    4056957 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Signal Estimation using Multiple-Wavelet Representations and Gaussian Models

    Deng, G. | British Library Conference Proceedings | 2005


    Maximum Likelihood Parameter Estimation for Non-Gaussian Prior Signal Models

    Schultz, R. R. / Stevenson, R. L. / Lumsdaine, A. et al. | British Library Conference Proceedings | 1994


    Improving Urban Travel Time Estimation Using Gaussian Mixture Models

    Gemma, Andrea / Mannini, Livia / Crisalli, Umberto et al. | IEEE | 2024


    Estimation of non-Gaussian noise parameters in the wavelet domain using the moment-generating function

    Svihlik, J. / Fliegel, K. / Kukal, J. et al. | British Library Online Contents | 2012


    Hexagonal Wavelet Representations for Recognizaing Complex Annotations

    Laine, A. F. / Schuler, S. / Institute of Electrical and Electronics Engineers; Computer Society | British Library Conference Proceedings | 1994