Denoising of Nondestructive Examination Data Using Wavelet, Maximum Entropy, and Limited Differential Methods

Details Denoising of Nondestructive Examination Data Using Wavelet, Maximum Entropy, and Limited Differential Methods Denoising of Nondestructive Examination Data Using Wavelet, Maximum Entropy, and Limited Differential Methods

Apr 2006

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006aps..apr.d1015e&link_type=abstract

American Physical Society, APS April Meeting, April 22-26, 2006, abstract #D1.015

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A simple and original denoising method, the ``limited differential method,'' has been developed. The algorithm is based on iterated local-pixel-averaging, and is very effective for large-amplitude speckled noise on a smoother background signal. For noise of this type, tests on both noisy two- dimensional images and noisy ultrasonic-scattering data volumes clearly demonstrate the superiority of the method relative to three more complicated standard methods: Fourier processing, wavelet denoising, and maximum-entropy reconstruction.

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