Image denoising based on Gaussian and non-Gaussian assumption (Q2911901)
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scientific article; zbMATH DE number 6075905
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Image denoising based on Gaussian and non-Gaussian assumption |
scientific article; zbMATH DE number 6075905 |
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3 September 2012
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complex dual-tree discrete wavelet transform
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image denoising
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Image denoising based on Gaussian and non-Gaussian assumption (English)
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The authors present here an adaptive intra-scale noise removal scheme and estimate clean wavelet coefficients using new prior information with Bayesian estimation technique. The effectiveness of the algorithm proposed is compared with others. It is observed that the Gaussian assumption is very effective for the orthogonal wavelet transform and the non-Gaussian bivariate distribution (cf. [\textit{L. Sendur} et al., IEEE Signal Process. Lett. 9, 438--441 (2002)]) is very effective for complex wavelet coefficients.
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