extractimf2d: Bidimensional Intrinsic Mode Function

In EMD: Empirical Mode Decomposition and Hilbert Spectral Analysis

Description

This function extracts the bidimensional intrinsic mode function from given an image utilizing extrema detection based on the equivalence relation between neighboring pixels.

Usage

extractimf2d(residue, x=NULL, y=NULL, nnrow=nrow(residue), 
    nncol=ncol(residue), tol=sd(c(residue))*0.1^2, 
    max.sift=20, boundary="reflexive", boundperc=0.3,  
    sm="none", spar=NULL, weight=NULL, check=FALSE)

Arguments

residue	matrix of an image observed at (x, y)
x, y	locations of regular grid at which the values in residue are measured
nnrow	the number of row of an input image
nncol	the number of column of an input image
tol	tolerance for stopping rule of sifting
max.sift	the maximum number of sifting
boundary	specifies boundary condition from “none", “symmetric" or “reflexive".
boundperc	expand an image by adding specified percentage of image at the boundary when boundary condition is 'symmetric' or 'reflexive'.
sm	specifies whether envelop is constructed by interpolation, thin-plate smoothing, Kriging, local polynomial smoothing, or loess. Use “none" for interpolation, “Tps" for thin-plate smoothing, “mKrig" for Kriging, “locfit" for local polynomial smoothing, or “loess" for loess.
spar	specifies user-supplied smoothing parameter of thin-plate smoothing, Kriging, local polynomial smoothing, or loess.
weight	deprecated.
check	specifies whether the sifting process is displayed. If check=TRUE, click the plotting area to start the next step.

Details

This function extracts the bidimensional intrinsic mode function from given image utilizing extrema detection based on the equivalence relation between neighboring pixels. See Kim et al. (2012) for detalis. See Kim et al. (2012) for detalis.

Value

imf	two dimensional IMF
residue	residue signal after extracting the finest IMF from residue
maxindex	index of maxima
minindex	index of minima
niter	number of iteration obtaining the IMF

References

Huang, N. E., Shen, Z., Long, S. R., Wu, M. L. Shih, H. H., Zheng, Q., Yen, N. C., Tung, C. C. and Liu, H. H. (1998) The empirical mode decomposition and Hilbert spectrum for nonlinear and nonstationary time series analysis. Proceedings of the Royal Society London A, 454, 903–995.

Kim, D., Park, M. and Oh, H.-S. (2012) Bidimensional Statistical Empirical Mode Decomposition. IEEE Signal Processing Letters, 19, 191–194, doi: 10.1109/LSP.2012.2186566.

See Also

extrema2dC, emd2d.

Examples

data(lena)
z <- lena[seq(1, 512, by=4), seq(1, 512, by=4)]

## Not run: 
lenaimf1 <- extractimf2d(z, check=FALSE)
## End(Not run)

EMD documentation built on Jan. 4, 2022, 1:08 a.m.