Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Fast and Adaptive Bidimensional Empirical Mode Decomposition Using Order-Statistics Filter Based Envelope Estimatio | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 728356 18 pages doi 2008 728356 Research Article Fast and Adaptive Bidimensional Empirical Mode Decomposition Using Order-Statistics Filter Based Envelope Estimation Sharif M. A. Bhuiyan Reza R. Adhami and Jesmin F. Khan Department of Electrical and Computer Engineering University of Alabama in Huntsville 272 Engineering Building Huntsville AL 35899 USA Correspondence should be addressed to Sharif M. A. Bhuiyan bhuiyas@ Received 17 August 2007 Revised 24 January 2008 Accepted 27 February 2008 Recommended by Nii Attoh-Okine 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. Copyright 2008 Sharif M. A. Bhuiyan et al. 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. 1. INTRODUCTION Empirical mode decomposition EMD originally developed by Huang et al. 1 2 is a data driven signal .
