The minimum-variance filter and smoother are generalized to include Poisson-distributed measurement noise components. It is shown that the resulting filtered and smoothed estimates are unbiased. The use of the filter and smoother within expectation-maximization algorithms are described for joint estimation of the signal and Poisson noise intensity. Conditions for the monotonicity and asymptotic convergence of the Poisson intensity iterates are also established. An image restoration example is presented that demonstrates improved estimation performance at low signal-to-noise ratios.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Iterative filtering and smoothing of measurements possessing poisson noise


    Beteiligte:
    Einicke, G. A. (Autor:in)


    Erscheinungsdatum :

    01.07.2015


    Format / Umfang :

    369741 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





    Re-entry filtering, prediction, and smoothing

    Wagner, W.E. | Engineering Index Backfile | 1966


    Iterative path integral approach to nonlinear stochastic optimal control under compound poisson noise

    Yuta, Okumura / Kashima, Kenji / Ohta, Yoshito | British Library Online Contents | 2017