Modeling the Marginal Distributions of Complex Wavelet Coefficient Magnitudes for the Classification of Zoom-Endoscopy Images

In this paper, we propose a set of new image features for the classification of zoom-endoscopy images. The feature extraction step is based on fitting a two-parameter Weibull distribution to the wavelet coefficient magnitudes of sub-bands obtained from a complex wavelet transform variant. We show, that the shape and scale parameter possess more discriminative power than the classic mean and standard deviation based features for complex subband coefficient magnitudes. Furthermore, we discuss why the commonly used Rayleigh distribution model is suboptimal in our case.

[1]  Andreas Uhl,et al.  Pit pattern classification of zoom-endoscopic colon images using wavelet texture features , 2006 .

[2]  S. Mitra,et al.  Texture classification using dual-tree complex wavelet transform , 1999 .

[3]  N. Kingsbury.  Complex Wavelets for Shift Invariant Analysis and Filtering of Signals , 2001 .

[4]  M. Hafner,et al.  Pit Pattern Classification of Zoom-Endoscopic Colon Images using Histogram Techniques , 2006, Proceedings of the 7th Nordic Signal Processing Symposium - NORSIG 2006.

[5]  Dimitris A. Karras,et al.  Computer Methods and Programs in Biomedicine , 2022 .

[6]  Nick G. Kingsbury,et al.  Complex wavelet features for fast texture image retrieval , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[7]  Nick Kingsbury,et al.  The dual-tree complex wavelet transform: a new technique for shift invariance and directional filters , 1998 .

[8]  David G. Stork,et al.  Pattern Classification , 1973 .

[9]  Karel J. Zuiderveld,et al.  Contrast Limited Adaptive Histogram Equalization , 1994, Graphics Gems.

[10]  Dimitris A. Karras,et al.  Computer-aided tumor detection in endoscopic video using color wavelet features , 2003, IEEE Transactions on Information Technology in Biomedicine.

[11]  S. E. Ahmed,et al.  Handbook of Statistical Distributions with Applications , 2007, Technometrics.

[12]  Shigeo Abe DrEng.  Pattern Classification , 2001, Springer London.

[13]  Richard Baraniuk,et al.  The Dual-tree Complex Wavelet Transform , 2007 .

[14]  H. Lilliefors.  On the Kolmogorov-Smirnov Test for Normality with Mean and Variance Unknown , 1967 .

[15]  Nick G. Kingsbury,et al.  A dual-tree complex wavelet transform with improved orthogonality and symmetry properties , 2000, Proceedings 2000 International Conference on Image Processing (Cat. No.00CH37101).

[16]  S. Kudo,et al.  Colorectal tumours and pit pattern. , 1994, Journal of clinical pathology.

[17]  R. E. Wheeler.  Statistical distributions , 1983, APLQ.

[18]  Heekuck Oh,et al.  Neural Networks for Pattern Recognition , 1993, Adv. Comput..

[19]  M. Evans.  Statistical Distributions , 2000 .

[20]  Nick G. Kingsbury,et al.  Unsupervised image segmentation via Markov trees and complex wavelets , 2002, Proceedings. International Conference on Image Processing.

[21]  Justin K. Romberg,et al.  Multiscale classification using complex wavelets , 2000 .

[22]  S. Kudo,et al.  Diagnosis of colorectal tumorous lesions by magnifying endoscopy. , 1996, Gastrointestinal endoscopy.