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Quaternionic wavelets for texture classification
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DOI：10.1016/j.patrec.2011.06.028.png)
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Abstract
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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 217 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. (C) 2011 Elsevier B.V. All rights reserved.
Keywords:
Wavelet transform
2D Phase
Quaternionic Wavelet Transform
Image texture analysis
Image classification
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