Image restoration based on adaptive MCMC particle filter

Hui Tian*, Tingzhi Shen, Bing Hao, Yu Hu, Nan Yang

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    4 Citations (Scopus)

    Abstract

    In this paper, particle filter is applied in image restoration which can be posed as a recursive Bayesian estimation problem, in order to remove degeneracy phenomenon and alleviate the sample impoverishment problem, the convergence of Markov chain Monte Carlo (MCMC) method is introduced and used in resampling step, meanwhile a simple KLD sampling which separated from resampling step is combined to overcome the drawback of computational complexity by adapting the size of particle set. These improvements enhance the robustness, accuracy and flexibility of the particle filter, thus a new image restoration algorithm based on adaptive MCMC particle filter is proposed, the simulation results show the effectiveness of the proposed algorithm and present the superior performance over conventional particle filter.

    Original languageEnglish
    Title of host publicationProceedings of the 2009 2nd International Congress on Image and Signal Processing, CISP'09
    DOIs
    Publication statusPublished - 2009
    Event2009 2nd International Congress on Image and Signal Processing, CISP'09 - Tianjin, China
    Duration: 17 Oct 200919 Oct 2009

    Publication series

    NameProceedings of the 2009 2nd International Congress on Image and Signal Processing, CISP'09

    Conference

    Conference2009 2nd International Congress on Image and Signal Processing, CISP'09
    Country/TerritoryChina
    CityTianjin
    Period17/10/0919/10/09

    Keywords

    • Adptive
    • Image restoration
    • KLD-sampling
    • MCMC
    • Particle filter

    Fingerprint

    Dive into the research topics of 'Image restoration based on adaptive MCMC particle filter'. Together they form a unique fingerprint.

    Cite this