M -band filter banks and dual-tree wavelets for engine combustion and geophysical image analysis
Laurent C. Duval, Caroline Chaux, Jean‐Christophe Pesquet · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
Signals and images in industrial applications are often subject to strong disturbances and thus require robust methods for their analysis. Since these data are often non-stationary, time-scale or time-frequency tools have demonstrated effectiveness in their handling. More specifically, wavelet transforms and other filter bank generalizations are particularly suitable, due to their discrete implementation. We have recently investigated a specific family of filter banks, the M-band dual-tree wavelet, which provides state of the art performance for image restoration. It generalizes an Hilbert pair based decomposition structure, first proposed by N. Kingsbury and further investigated by I. Selesnick. In this work, we apply this frame decomposition to the analysis of two examples of signals and images in an industrial context: detection of structures and noises in geophysical images and the comparison of direct and indirect measurements resulting from engine combustion.