Quaternionic wavelets for texture classification

Raphaël Soulard (1) , Philippe Carré (1)

1 SIC

This article proposes a study of the recent quaternionic wavelet transform (QWT) from a practical point of view through a digital image analysis application. Based on a theoretic 2D generalization of the analytic signal leading to a strong 2D signal modeling, this representation uses actual 2D analytic wavelets and yields subbands having a shift-invariant magnitude and a 3-angle phase, using the quaternion algebra. Our experiment furthers the understanding of this quite sophisticated tool, and shows its practical interest by a clear improvement of a famous wavelet application: texture classification. Thanks to coherent multiscale analysis brought by the QWT we obtain better classification results than with standard wavelets in a similar process.

Mots clés: Wavelet transform; 2D Phase; Quaternionic Wavelet Transform; Image texture analysis; Image classification

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Raphaël Soulard, Philippe Carré. Quaternionic wavelets for texture classification. Pattern Recognition Letters, 2011, 32 (13), pp.1669--1678. ⟨10.1016/j.patrec.2011.06.028⟩. ⟨hal-00618159⟩