Introducing the locally stationary dual-tree complex wavelet model

Nelson, J. D. B. and Gibberd, A. J. (2016) Introducing the locally stationary dual-tree complex wavelet model. In: 2016 IEEE International Conference on Image Processing (ICIP) :. IEEE, USA, pp. 3583-3587. ISBN 9781467399623

[thumbnail of 2016_icip_nelson]
Preview
PDF (2016_icip_nelson)
2016_icip_nelson.pdf - Accepted Version
Available under License Creative Commons Attribution-NonCommercial.

Download (578kB)

Abstract

This paper reconciles Kingsbury's dual-tree complex wavelets with Nason and Eckley's locally stationary model. We here establish that the dual-tree wavelets admit an invertible de-biasing matrix and that this matrix can be used to invert the covariance relation. We also show that the added directional selectivity of the proposed model adds utility to the standard two-dimensional local stationary model. Non-stationarity detection on random fields is used as a motivating example. Experiments confirm that the dual-tree model can distinguish anisotropic non-stationarities significantly better than the current model.

Item Type:
Contribution in Book/Report/Proceedings
Additional Information:
©2016 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
ID Code:
128564
Deposited By:
Deposited On:
06 Nov 2018 15:32
Refereed?:
Yes
Published?:
Published
Last Modified:
31 Dec 2023 01:37