extractimf2d {EMD} | R Documentation |
This function extracts two dimensional intrinsic mode function from given an image.
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, weight=0, check=FALSE)
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'. |
weight |
the smoothness of thin plate spline is determined by weight times smoothing parameter of GCV. |
check |
specifies whether the sifting process is displayed. If check=TRUE , click the plotting area to start the next step. |
This function extracts two dimensional intrinsic mode function from given image. For sifting procee, thin plate spline is used.
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 |
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)] #lenaimf1 <- extractimf2d(z, check=FALSE)