Learn R Programming

EMD (version 1.5.9)

extrema2dC: Finding Local Extrema

Description

This function finds the bidimensional local extrema based on the equivalence relation between neighboring pixels.

Usage

extrema2dC(z, nnrow=nrow(z), nncol=ncol(z))

Arguments

z

matrix of an input image

nnrow

the number of row of an input image

nncol

the number of column of an input image

Value

minindex

index of minima. Each row specifies index of local minimum.

maxindex

index of maxima. Each row specifies index of local maximum.

Details

This function finds the bidimensional local extrema based on the equivalence relation between neighboring pixels. See Kim et al. (2012) for detalis.

References

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

extrema, , extractimf2d, emd2d.

Examples

Run this code
# NOT RUN {
data(lena)
z <- lena[seq(1, 512, by=4), seq(1, 512, by=4)]

par(mfrow=c(1,3), mar=c(0, 0.5, 2, 0.5))
image(z, main="Lena", xlab="", ylab="", col=gray(0:100/100), axes=FALSE)    

example <- extrema2dC(z=z)
localmin <- matrix(256, 128, 128)
localmin[example$minindex] <- z[example$minindex]
image(localmin, main="Local minimum", xlab="", ylab="", col=gray(0:100/100), axes=FALSE)

localmax <- matrix(0, 128, 128)
localmax[example$maxindex] <- z[example$maxindex]
image(localmax, main="Local maximum", xlab="", ylab="", col=gray(0:100/100), axes=FALSE)
# }

Run the code above in your browser using DataLab