Treating Color Image with imagerExtra
In imagerExtra: Extra Image Processing Library Based on 'imager'

knitr::opts_chunk$set(warning=FALSE, message=FALSE, cache=FALSE, 
               comment=NA, verbose=TRUE, fig.width=7.5, fig.height=5, dev='jpeg',dev.args=list(quality=50)) 
library(imager)
res <- vector("list",3)
a <- imfill(300, 300, 3, c(1,0,0)) %>% grayscale()
res[[1]] <- unique(a)
a <- imfill(300, 300, 3, c(0,1,0)) %>% grayscale()
res[[2]] <- unique(a)
a <- imfill(300, 300, 3, c(0,0,1)) %>% grayscale()
res[[3]] <- unique(a)

We have two options when treating color images with imagerExtra.

process the channels independently
preserve the hue of image, process the intensity component and then compute RGB values from the new intensity component

The former is straightforward.

One example is shown below.

library(imagerExtra)
x <- boats
s <- 0.1
R(x) <- BalanceSimplest(R(x), s, s, range=c(0,1))
G(x) <- BalanceSimplest(G(x), s, s, range=c(0,1))
B(x) <- BalanceSimplest(B(x), s, s, range=c(0,1))
layout(matrix(1:2, 1, 2))
plot(boats, main = "Original")
plot(x, main = "Independently Processed")

The latter needs three functions: Grayscale, GetHue, RestoreHue.

Grayscale: computes average of RGB channel
GetHue: stores hue of image
RestoreHue: restores hue of image

grayscale function of imager computes as shown below by default.

text1 <- sprintf("Y = %fR + %fG + %fB", res[[1]], res[[2]], res[[3]])
cat(text1)

where Y is grayscale value, R is R value, G is G value, and B is B value.

This equation reflects the way of human visual perception.

This grayscale conversion makes it difficult to restore hue of image.

That's why we need Grayscale function, which just compute average of RGB channels.

How to use these functions is shown below.

g <- Grayscale(boats)
hueim <- GetHue(boats)
g <- BalanceSimplest(g, s, s, range=c(0,1))
y <- RestoreHue(g, hueim)
layout(matrix(1:2, 1, 2))
plot(boats, main = "Original")
plot(y, main = "Processed While Preserving Hue")