blurHeat | R Documentation |
Blur a Pixel Image by Applying Diffusion
blurHeat(X, ...)
## S3 method for class 'im'
blurHeat(X, sigma, ...,
connect = 8, symmetric = FALSE, k= 1, show = FALSE)
## S3 method for class 'im'
SmoothHeat(X, sigma, ...)
X |
Pixel image (object of class |
sigma |
Smoothing bandwidth. A numeric value, a pixel image or
a |
... |
Ignored by |
connect |
Grid connectivity: either 4 or 8. |
symmetric |
Logical value indicating whether to force the algorithm to use a symmetric random walk. |
k |
Integer. Calculations will be performed by repeatedly multiplying
the current state by the |
show |
Logical value indicating whether to plot successive iterations. |
The function blurHeat
is generic.
This help file documents the method blurHeat.im
for pixel images
(objects of class "im"
). This is currently equivalent
to SmoothHeat.im
, which is also documented here.
If sigma
is a numeric value, then
the classical time-dependent heat equation is solved
up to time t = sigma^2
starting with the initial
condition given by the image X
. This has the effect
of blurring the input image X
.
If sigma
is a function or a pixel image, then
it is treated as a spatially-variable diffusion rate,
and the corresponding heat equation is solved.
This command can be used to calculate the expected value
of the diffusion estimator of intensity (densityHeat
)
when the true intensity is known.
A pixel image on the same raster as X
.
.
densityHeat
,
blur
.
Z <- as.im(function(x,y) { sin(10*x) + sin(9*y) }, letterR)
ZZ <- blurHeat(Z, 0.2)
plot(solist(original=Z, blurred=ZZ), main="")
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