A new algorithm based on facet model and Particle filter is presented to detect infrared small moving target in image sequence. Firstly, it utilizes a Bayesian based particle filter method to track the target in image sequence and get the target search window. Then the detection is performed on the image intensity surface of search window fitted by cubic facet model. The new partial derivative operators are exploited according to cubic facet model to detect maximum intensity points from search window, which correspond to the small target position in image. Experimental results with the infrared image sequence show that the proposed algorithm can successfully detect the small target, the real-time and anti-noise performance of the algorithm are better than traditional algorithms.


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    Title :

    Infrared Small Moving Target Detection Using Facet Model and Particle Filter


    Contributors:
    Yu, Yong (author) / Guo, Lei (author)


    Publication date :

    2008-05-01


    Size :

    591767 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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