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W1983606427 abstract "We reduced noise in images using a higher-order, correlation-based method. In this approach, wavelet coefficients were classified as either mostly noise or mostly signal based on third-order statistics. Because the higher than second-order moments of the Gaussian probability function are zero, the third-order correlation coefficient may not have a statistical contribution from Gaussian noise. Using a detection algorithm derived from third-order statistics, we determined if a wavelet coefficient was noisy by looking at its third-order correlation coefficient. Using imagery of space shuttle tiles, our results showed that the minimum mean-squared error obtained using third-order statistics was often less than that using second-order statistics." @default.
W1983606427 created "2016-06-24" @default.
W1983606427 creator A5065755721 @default.
W1983606427 date "2006-10-18" @default.
W1983606427 modified "2023-09-23" @default.
W1983606427 title "Denoising of imagery for inspection tasks using higher-order statistics" @default.
W1983606427 doi "https://doi.org/10.1117/12.686619" @default.
W1983606427 hasPublicationYear "2006" @default.
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