A New Two-dimensional Empirical Mode Decomposition Based on Classical Empirical Mode Decomposition and Radon Transform

Empirical mode decomposition is a method to decompose signals proposed by N.E.Huang et. al in 1998. It can extract adaptively the oscillatory modes at each time from a complex signal, namely it can decompose the signal into a finite (often less) number of intrinsic mode functions (IMFs). With Hilbert transform, the IMFs yield instantaneous frequencies as functions of time, that give sharp identifications of embedded structures. The final presentation of the results is a time-frequency-energy distribution, designated as the Hilbert spectrum and the new method for signal processing is called as Hilbert-Huang transform(HHT)[1]. Being different from Fourier decomposition and wavelet decomposition, EMD has no specified ”basis”. Its ”basis” is adaptively produced depending on the signal itself, which brings not only high decomposition efficiency but also sharp frequency and time localization. A key point is that the signal analysis based on HHT is physically significant. Because of its excellence, HHT has been utilized and studied widely by researchers and experts in signal processing and other related fields. In recent years, more and more works on HHT theory are reported such as [5, 6, 7, 2, 8]. Its application have spread from earthquake research, ocean science, biomedicine, speech signal analysis to image analysis and processing [9, 10, 11, 12, 13, 14, 4, 15, 16].