imager package in R and example References: http://dahtah.github.io/imager/ http://dahtah.github.io/imager/imager.html https://cran.r-project.org/web/packages/imager/imager.pdf

1. Prepared by Volkan OBAN
Loading a picture (.png) on R
> library(png)
> img = readPNG("itu.png")
> if (exists("rasterImage")) { # can plot only in R 2.11.0 and higher
plot(1:2, type='n')
if (names(dev.cur()) == "windows") {
# windows device doesn't support semi-transparency so we'll need
# to flatten the image
transparent <- img[,,4] == 0
img <- as.raster(img[,,1:3])
img[transparent] <- NA
rasterImage(img, 1.2, 1.27, 1.8, 1.73, interpolate=FALSE)
} else {
# any reasonable device will be fine using alpha
rasterImage(img, 1.2, 1.27, 1.8, 1.73)
rasterImage(img.n, 1.5, 1.5, 1.9, 1.8)
}
}

2. Reference: https://github.com/dahtah/imager
http://dahtah.github.io/imager/gettingstarted.html
https://www.r-bloggers.com/new-package-for-image-processing-in-r/
http://stackoverflow.com/questions/15283447/how-to-read-jpeg-in-r-2-15
imager package in R

3. Example:
> library(imager)
> im <- load.image(system.file('extdata/parrots.png',package='imager'))
> layout(t(1:3))
> plot(im,main="Original image")
> grad <- grayscale(im) %>% get_gradient("xy")
> names(grad) <- paste("Gradient along",c("x","y"))
> l_ply(names(grad),function(n) plot(grad[[n]],main=n))

4. Example:
> library(imager)
> plot(boats)

5. > layout(t(1:2))
> plot(boats)
> plot(boats/2)

6. layout(t(1:2))
> boats.s <- boats/255 #scale to 0..1
> plot(boats.s,rescale=FALSE)
> plot(boats.s/2,rescale=FALSE)

7. > rgb(0,1,0)
[1] "#00FF00"
> cscale <- function(r,g,b) rgb(g,r,b)
> plot(boats.s,colourscale=cscale,rescale=FALSE)

8. > cscale <- scales::gradient_n_pal(c("red","purple","lightblue"),c(0,.5,1))
> #cscale is now a function returning colour codes
> cscale(0)
[1] "#FF0000"
> grayscale(boats) %>% plot(colourscale=cscale,rescale=FALSE)
> grayscale(boats) %>% plot(colourscale=cscale,rescale=FALSE)

9. > boats.g <- grayscale(boats)
> f <- ecdf(boats.g)
> plot(f,main="Empirical CDF of luminance values")
> f <- ecdf(boats.g)
> plot(f,main="Empirical CDF of luminance values")
> f(boats.g) %>% str
num [1:98304] 0.175 0.169 0.168 0.168 0.17 ...
> f(boats.g) %>% as.cimg(dim=dim(boats.g)) %>% plot(main="With histogram equalisation")

10. > gr <- imgradient(boats.g,"xy")
> plot(gr,layout="row")

11. > dx <- imgradient(boats.g,"x")
> dy <- imgradient(boats.g,"y")
> grad.mag <- sqrt(dx^2+dy^2)
> plot(grad.mag,main="Gradient magnitude")

12. library(ggplot2)
> df <- grayscale(boats) %>% as.data.frame
> p <- ggplot(df,aes(x,y))+geom_raster(aes(fill=value))
> p

13. > df <- as.data.frame(boats)
> p <- ggplot(df,aes(x,y))+geom_raster(aes(fill=value))+facet_wrap(~ cc)
> p+scale_y_reverse()

14. Example:
>hub <- load.example("hubble") %>% grayscale
> plot(hub,main="Hubble Deep Field")

15. Example:
fpath <- system.file('extdata/parrots.png',package='imager')
> parrots <- load.image(fpath)
> plot(parrots)

16. Example:
> library(imager)
> library(purrr)
> parrots <- load.example("parrots")
> plot(parrots)
> #Define a function that converts to YUV, blurs a specific channel, and co
nverts back
> bchan <- function(im,ind,sigma=5) {
+ im <- RGBtoYUV(im)
+ channel(im,ind) <- isoblur(channel(im,ind),sigma);
+ YUVtoRGB(im)
+ }
> #Run the function on all three channels and collect the results as a list
> blurred <- map_il(1:3,~ bchan(parrots,.))
> names(blurred) <- c("Luminance blur (Y)","Chrominance blur (U)","Chromina
nce blur (V)")
> plot(blurred