Two-Dimensional Discrete Wavelet Transform
Performs a separable two-dimensional discrete wavelet transform (DWT) on a matrix of dyadic dimensions.
dwt.2d(x, wf, J = 4, boundary = "periodic") idwt.2d(y)
x |
input matrix (image) |
wf |
name of the wavelet filter to use in the decomposition |
J |
depth of the decomposition, must be a number less than or equal to log(min{M,N},2) |
boundary |
only |
y |
an object of class |
See references.
List structure containing the 3J+1 sub-matrices from the decomposition.
B. Whitcher
Mallat, S. (1998) A Wavelet Tour of Signal Processing, Academic Press.
Vetterli, M. and J. Kovacevic (1995) Wavelets and Subband Coding, Prentice Hall.
## Xbox image
data(xbox)
xbox.dwt <- dwt.2d(xbox, "haar", 3)
par(mfrow=c(1,1), pty="s")
plot.dwt.2d(xbox.dwt)
par(mfrow=c(2,2), pty="s")
image(1:dim(xbox)[1], 1:dim(xbox)[2], xbox, xlab="", ylab="",
main="Original Image")
image(1:dim(xbox)[1], 1:dim(xbox)[2], idwt.2d(xbox.dwt), xlab="", ylab="",
main="Wavelet Reconstruction")
image(1:dim(xbox)[1], 1:dim(xbox)[2], xbox - idwt.2d(xbox.dwt),
xlab="", ylab="", main="Difference")
## Daubechies image
data(dau)
par(mfrow=c(1,1), pty="s")
image(dau, col=rainbow(128))
sum(dau^2)
dau.dwt <- dwt.2d(dau, "d4", 3)
plot.dwt.2d(dau.dwt)
sum(plot.dwt.2d(dau.dwt, plot=FALSE)^2)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.