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Proceedings Paper

Denoising of imagery for inspection tasks using higher-order statistics
Author(s): Samuel P. Kozaitis
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Paper 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.

Paper Details

Date Published: 12 October 2006
PDF: 10 pages
Proc. SPIE 6383, Wavelet Applications in Industrial Processing IV, 63830J (12 October 2006); doi: 10.1117/12.686619
Show Author Affiliations
Samuel P. Kozaitis, Florida Institute of Technology (United States)


Published in SPIE Proceedings Vol. 6383:
Wavelet Applications in Industrial Processing IV
Frédéric Truchetet; Olivier Laligant, Editor(s)

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