catmssim_2d | R Documentation |
The categorical structural similarity index measure for 2D categorical or binary images for multiple scales. The default is to compute over 5 scales.
catmssim_2d(
x,
y,
levels = NULL,
weights = NULL,
window = 11,
method = "Cohen",
...,
random = "random"
)
x , y |
a binary or categorical image |
levels |
how many levels of downsampling to use. By default, 5. If
|
weights |
a vector of weights for the different scales. By default,
equal to |
window |
by default 11 for 2D and 5 for 3D images,
but can be specified as a
vector if the window sizes differ by dimension.
The vector must have the same number of
dimensions as the inputted |
method |
whether to use Cohen's kappa ( |
... |
additional constants can be passed to internal functions. |
random |
whether to have deterministic PRNG ( |
a value less than 1 indicating the similarity between the images.
set.seed(20181207)
x <- matrix(sample(0:3, 128^2, replace = TRUE), nrow = 128)
y <- x
for (i in 1:128) y[i, i] <- 0
for (i in 1:127) y[i, i + 1] <- 0
catmssim_2d(x, y, method = "Cohen", levels = 2) # the default
# now using a different similarity score (Jaccard Index)
catmssim_2d(x, y, method = "NMI")
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