2011 | OriginalPaper | Buchkapitel
Complex Wavelet Transform Variants in a Scale Invariant Classification of Celiac Disease
verfasst von : Andreas Uhl, Andreas Vécsei, Georg Wimmer
Erschienen in: Pattern Recognition and Image Analysis
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
In this paper, we present variants of the Dual-Tree Complex Wavelet Transform (DT-CWT) in order to automatically classify endoscopic images with respect to the Marsh classification. The feature vectors either consist of the means and standard deviations of the subbands from a DT-CWT variant or of the Weibull parameter of these subbands. To reduce the effects of different distances and perspectives toward the mucosa, we enhanced the scale invariance by applying the discrete Fourier transform or the discrete cosine transform across the scale dimension of the feature vector.