emd2d {EMD}R Documentation

Two dimensional Empirical Mode Decomposition

Description

This function performs two dimensional empirical mode decomposition.

Usage

emd2d(z, x = NULL, y = NULL, tol = sd(c(z)) * 0.1^2, max.sift = 20, 
    boundary = "reflexive", boundperc = 0.3, max.imf = 5,  
    smlevels = 1, weight = 0, plot.imf = FALSE) 

Arguments

z matrix of an image observed at (x, y)
x, y locations of regular grid at which the values in z are measured
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'.
max.imf the maximum number of IMF's
smlevels specifies which level of the IMF is obtained by smoothing other than interpolation.
weight the smoothness of a thin plate spline is determined by weight times smoothing parameter of GCV.
plot.imf specifies whether each IMF is displayed. If plot.imf=TRUE, click the plotting area to start the next step.

Details

This function performs two dimensional empirical mode decomposition.

Value

imf two dimensional IMF's
residue residue image after extracting the IMF's
maxindex index of maxima
minindex index of minima
nimf number of IMF's

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.

See Also

extrema2dC, extractimf2d.

Examples

data(lena)
z <- lena[seq(1, 512, by=4), seq(1, 512, by=4)]
image(z, main="Lena", xlab="", ylab="", col=gray(0:100/100), axes=FALSE)
#lenadecom <- emd2d(z, max.imf = 4)
#imageEMD(z=z, emdz=lenadecom, extrema=TRUE, col=gray(0:100/100))

[Package EMD version 1.2.0 Index]