||The Study of Improved Empirical Mode Decomposition
||Institute of Computer Science and Information Engineering
Empirical mode decomposition
Mode mixing phenomenon
2D mode mixing phenomenon
Intrinsic mode function
In the sifting process of the traditional empirical mode decomposition (EMD), intermittence causes mode mixing phenomenon. The intrinsic mode function (IMF) with the mode mixing phenomenon loses its original real physical meaning. In the current study, an improved EMD based on time scale allocation method has been proposed to improve the decomposition of the mode mixing phenomenon fast and stably. Additionally, the 2D version of our method has been extended to improve the decomposition of the mode mixing phenomenon in the 2D image data. Experimental results show that the improved EMD not only improves the decomposition of the mode mixing phenomenon correctly regardless for 1D signal or 2D image, but also exhibits great performance in quality and computation time. Furthermore, this thesis discusses the mode mixing phenomenon for 2D image data directly rather than extending the definition form 1D to 2D.
Table of Contents IV
List of Acronyms VI
List of Talbes VII
List of Figures VIII
Chapter 1 Introduction 1
Chapter 2 Background 4
2.1 1D Algorithm 4
2.2 2D Algorithm 11
Chapter 3 Mode Mixing Phenomenon 14
3.1 1D Mode Mixing Phenomenon 14
3.2 2D Mode Mixing Phenomenon 16
Chapter 4 Proposed Method 22
4.1 The Judgement Method Based on the Time Scale 24
4.2 The Improved EMD with TSA Step 27
4.3 Multi-dimensional TSAEMD (MTSAEMD) 29
Chapter 5 Experimental Results and Comparisons 30
5.1 1D Artificial Signals 30
5.2 2D Standard Test Images 48
Chapter 6 Conclusions 58
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