Complex Wavelet Transform variants and Discrete Cosine Transform for scale invariance in magnification-endoscopy image classification

In this paper, scale invariant features are extracted from different variants of the Dual-Tree Complex Wavelet Transform (DT-CWT) in order to classify high-magnification colon endoscopy imagery with respect to the pit pattern scheme. To enhance the scale invariance, the Discrete Cosine Transform is applied to the feature vectors, that are achieved from a DT-CWT variant. The feature vectors either consist of the means and standard deviations of the subbands from a DTC-WT variant or of the Weibull parameter of these subbands. Superior results as compared to techniques described previously in literature are reported.