imager.combine: Combining images
In imager: Image Processing Library Based on 'CImg'

imager.combine

R Documentation

Combining images

Description

These functions take a list of images and combine them by adding, multiplying, taking the parallel min or max, etc. The max. in absolute value of (x1,x2) is defined as x1 if (|x1| > |x2|), x2 otherwise. It's useful for example in getting the most extreme value while keeping the sign. "parsort","parrank" and "parorder" aren't really reductions because they return a list of the same size. They perform a pixel-wise sort (resp. order and rank) across the list.

Usage

add(x, na.rm = FALSE)

wsum(x, w, na.rm = FALSE)

average(x, na.rm = FALSE)

mult(x, na.rm = FALSE)

parmax(x, na.rm = FALSE)

parmax.abs(x)

parmin.abs(x)

parmin(x, na.rm = FALSE)

enorm(x)

parmed(x, na.rm = FALSE)

parquan(x, prob = 0.5, na.rm = FALSE)

parvar(x, na.rm = FALSE)

parsd(x, na.rm = FALSE)

parall(x)

parany(x)

equal(x)

which.parmax(x)

which.parmin(x)

parsort(x, increasing = TRUE)

parorder(x, increasing = TRUE)

parrank(x, increasing = TRUE)

Arguments

`x`	a list of images
`na.rm`	ignore NAs (default FALSE)
`w`	weights (must be the same length as the list)
`prob`	probability level for parquan, default of 0.5 returns the median
`increasing`	if TRUE, sort in increasing order (default TRUE)

Details

parvar returns an unbiased estimate of the variance (as in the base var function). parsd returns the square root of parvar. parquan returns the specified quantile, and defines this in the same manner as the default R quantile function (type = 7). Using parmed and parquan with quan = 0.5 will return the same result, but parmed will be slightly faster (but only a few percent).

To correctly use multiple threads users should set nthreads in cimg.use.openmp. You also need to be careful that this is not higher than the value in the system environment variable OMP_THREAD_LIMIT (this can be checked with Sys.getenv('OMP_THREAD_LIMIT')). The OMP_THREAD_LIMIT thread limit usually needs to be correctly set before launching R, so using Sys.setenv once a session has started is not certain to work.

Functions

add(): Add images
wsum(): Weighted sum of images
average(): Average images
mult(): Multiply images (pointwise)
parmax(): Parallel max over images
parmax.abs(): Parallel max in absolute value over images,
parmin.abs(): Parallel min in absolute value over images,
parmin(): Parallel min over images
enorm(): Euclidean norm (i.e. sqrt(A^2 + B^2 + ...))
parmed(): Parallel Median over images
parquan(): Parallel Quantile over images
parvar(): Variance
parsd(): Std. deviation
parall(): Parallel all (for pixsets)
parany(): Parallel any (for pixsets)
equal(): Test equality
which.parmax(): index of parallel maxima
which.parmin(): index of parallel minima
parsort(): pixel-wise sort
parorder(): pixel-wise order
parrank(): pixel-wise rank

Author(s)

Simon Barthelme

Examples


im1 <- as.cimg(function(x,y) x,50,50)
im2 <- as.cimg(function(x,y) y,50,50)
im3 <- as.cimg(function(x,y) cos(x/10),50,50)
l <- imlist(im1,im2,im3)
add(l) %>% plot #Add the images
average(l) %>% plot #Average the images
mult(l) %>% plot #Multiply
wsum(l,c(.1,8,.1)) %>% plot #Weighted sum
parmax(l) %>% plot #Parallel max
parmin(l) %>% plot #Parallel min
parmed(l) %>% plot #Parallel median
parsd(l) %>% plot #Parallel std. dev
#parsort can also be used to produce parallel max. and min
(parsort(l)[[1]]) %>% plot("Parallel min")
(parsort(l)[[length(l)]]) %>% plot("Parallel max")
#Resize boats so the next examples run faster
im <- imresize(boats,.5)
#Edge detection (Euclidean norm of gradient)
imgradient(im,"xy") %>% enorm %>% plot
#Pseudo-artistic effects
l <- map_il(seq(1,35,5),~ boxblur(im,.))
parmin(l) %>% plot
average(l) %>% plot
mult(l) %>% plot
#At each pixel, which colour channel has the maximum value?
imsplit(im,"c") %>% which.parmax %>% table
#Same thing using parorder (ties are broken differently)!!!
imsplit(im,"c") %>% { parorder(.)[[length(.)]] } %>% table

imager documentation built on May 29, 2024, 1:38 a.m.