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    Homogeneity Localization Using Particle Filters With Application to Noise Estimation

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    Date
    2011-07
    Type
    Article
    Author
    Ghazal, Mohammed
    Aishy, Amer
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    Abstract
    This paper proposes a method for localizing homogeneity and estimating additive white Gaussian noise (AWGN) variance in images. The proposed method uses spatially and sparsely scattered initial seeds and utilizes particle filtering techniques to guide their spatial movement towards homogeneous locations. This way, the proposed method avoids the need to perform the full search associated with block-based noise estimation methods. To achieve this, the paper proposes for the particle filter a dynamic model and a homogeneity observation model based on Laplacian structure detectors. The variance of AWGN is robustly estimated from the variances of blocks in the detected homogeneous areas. A proposed adaptive trimmed-mean based robust estimator is used to account for the reduction in estimation samples from the full search approach. Our results show that the proposed method reduces the number of homogeneity measurements required by block-based methods while achieving more accuracy.
    URI
    https://dspace.adu.ac.ae/handle/1/1884
    DOI
    https://doi.org/10.1109/TIP.2010.2097272
    Citation
    Ghazal, M., & Amer, A. (2010). Homogeneity localization using particle filters with application to noise estimation. IEEE Transactions on image processing, 20(7), 1788-1796.
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