emd2d {EMD} | R Documentation |
This function performs two dimensional empirical mode decomposition.
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)
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. |
This function performs two dimensional empirical mode decomposition.
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 |
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.
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))