Paper
19 October 2006 M-band filter banks and dual-tree wavelets for engine combustion and geophysical image analysis
Laurent Duval, Caroline Chaux, Jean-Christophe Pesquet
Author Affiliations +
Proceedings Volume 6383, Wavelet Applications in Industrial Processing IV; 63830B (2006) https://doi.org/10.1117/12.691781
Event: Optics East 2006, 2006, Boston, Massachusetts, United States
Abstract
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.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Laurent Duval, Caroline Chaux, and Jean-Christophe Pesquet "M-band filter banks and dual-tree wavelets for engine combustion and geophysical image analysis", Proc. SPIE 6383, Wavelet Applications in Industrial Processing IV, 63830B (19 October 2006); https://doi.org/10.1117/12.691781
Lens.org Logo
CITATIONS
Cited by 1 scholarly publication.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Wavelets

Discrete wavelet transforms

Combustion

Image analysis

Wavelet transforms

Image filtering

Signal processing

Back to Top