Interpolation artifacts and bidimensional ensemble empirical mode decomposition

The empirical mode decomposition (EMD) method developed by Huang et al. (1998) is a powerful signal analysis technique for non-stationary and nonlinear systems. EMD decomposes a signal into a sum of intrinsic oscillatory components, called Intrinsic Mode Functions (IMFs). Each IMF has different frequency components, potentially highlighting different geologic and stratigraphic information (Magrin-Chagnolleau & Baraniuk, 1999; Han & Van der Baan, 2011). Furthermore, high-resolution time-frequency analysis is possible by combining EMD with the instantaneous frequency. The resulting time-frequency resolution promises to be significantly higher than that obtained using traditional time-frequency analysis tools, such as short time Fourier and wavelet transforms (Han and Van der Baan, 2013). Furthermore, Bekara & Van der Baan (2009) utilize EMD in frequency-distance (f-x) domain to suppress the random and coherent noise.