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- W1971071247 abstract "In this paper, a novel texture classification scheme using higher-order statistics (HOS) functions as discriminating features is proposed. It is well known that such statistical parameters are insensitive to additive Gaussian noise. In particular, third-order statistical parameters, i.e. third-order cumulants and bispectrum, are insensitive to any symmetrically distributed noise, and also exhibit the capability of better characterizing non-Gaussian signals. By exploiting these HOS properties, it is possible to devise a robust method for classifying textures affected by noise with different distributions and even with very low signal-to-noise ratios." @default.
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- W1971071247 date "1998-04-01" @default.
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- W1971071247 title "Noisy texture classification: A higher-order statistics approach" @default.
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- W1971071247 doi "https://doi.org/10.1016/s0031-3203(97)00055-1" @default.
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