imager (version 0.40.2)

imager.combine: 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. parvar returns an unbiased estimate of the variance (as in the base var function). parsd returns the square root of parvar.

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)
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)

increasing

if TRUE, sort in increasing order (default TRUE)

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: Median

• 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

See Also

imsplit,Reduce

Examples

# NOT RUN {
im1 <- as.cimg(function(x,y) x,100,100)
im2 <- as.cimg(function(x,y) y,100,100)
im3 <- as.cimg(function(x,y) cos(x/10),100,100)
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")
#Edge detection (Euclidean norm of gradient)
imgradient(boats,"xy") %>% enorm %>% plot
#Pseudo-artistic effects
l <- map_il(seq(1,35,5),~ boxblur(boats,.))
parmin(l) %>% plot
average(l) %>% plot
mult(l) %>% plot
#At each pixel, which colour channel has the maximum value?
imsplit(boats,"c") %>% which.parmax %>% table
#Same thing using parorder (ties are broken differently)!!!
imsplit(boats,"c") %>% { parorder(.)[[length(.)]] } %>% table
# }