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Parametric Gaussianization procedure of wavelet coefficients for texture retrieval

Abstract : In this paper, we deal with the problem of feature extraction in content-based image retrieval (CBIR) using statistical approach. A Gaussianization procedure based on parametric density assumptions of steerable pyramid coefficients is proposed. The extraction method of features including the Gaussianization step allows us to limit the order of the statistical model used to characterize the image textures. The performances of the proposed method are analyzed on a database of texture images and compared with the performances of other texture features proposed in previous works.
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https://hal.archives-ouvertes.fr/hal-00356294
Contributor : Yannick Berthoumieu Connect in order to contact the contributor
Submitted on : Tuesday, January 27, 2009 - 10:46:22 AM
Last modification on : Wednesday, January 31, 2018 - 1:46:02 PM

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Nour-Eddine Lasmar, Youssef Stitou, Soufiane Jouini, Yannick Berthoumieu, Mohamed Najim. Parametric Gaussianization procedure of wavelet coefficients for texture retrieval. ICASSP 2008. IEEE International Conference on Acoustics, Speech and Signal Processing, 2008., Apr 2008, Las Vegas, United States. pp.749-752, ⟨10.1109/ICASSP.2008.4517718⟩. ⟨hal-00356294⟩

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