Open Access

Fast and Adaptive Bidimensional Empirical Mode Decomposition Using Order-Statistics Filter Based Envelope Estimation

  • Sharif M. A. Bhuiyan1Email author,
  • Reza R. Adhami1 and
  • Jesmin F. Khan1
EURASIP Journal on Advances in Signal Processing20082008:728356

https://doi.org/10.1155/2008/728356

Received: 17 August 2007

Accepted: 27 February 2008

Published: 8 May 2008

Abstract

A novel approach for bidimensional empirical mode decomposition (BEMD) is proposed in this paper. BEMD decomposes an image into multiple hierarchical components known as bidimensional intrinsic mode functions (BIMFs). In each iteration of the process, two-dimensional (2D) interpolation is applied to a set of local maxima (minima) points to form the upper (lower) envelope. But, 2D scattered data interpolation methods cause huge computation time and other artifacts in the decomposition. This paper suggests a simple, but effective, method of envelope estimation that replaces the surface interpolation. In this method, order statistics filters are used to get the upper and lower envelopes, where filter size is derived from the data. Based on the properties of the proposed approach, it is considered as fast and adaptive BEMD (FABEMD). Simulation results demonstrate that FABEMD is not only faster and adaptive, but also outperforms the original BEMD in terms of the quality of the BIMFs.

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Authors’ Affiliations

(1)
Department of Electrical and Computer Engineering, University of Alabama in Huntsville

Copyright

© Sharif M. A. Bhuiyan et al. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.