Why is it much slower to load in a large image (~4MB) in R using the EBImage package, compared to matlab? is there anyway around this?
Note: I'm pretty sure EBImage is in some way a wrapper for imagemagick in R
in R:
system.time(im <- readImage("~/Desktop/image.jpg"))
Elapsed time is 10.935 seconds.
in Matlab:
tic;
im = imread('~/Desktop/image.jpg');
toc;
Elapsed time is 0.555381 seconds.
using the raster package
system.time(im <- brick('image.jpg'))
takes 0.264 seconds
When trying to get the values
system.time(vals <- getValues(im))
takes 8.617 seconds so I'm back to square one since I need to extract a channel
Edit 2
I ended up using the package jpeg which has function readJPEG and performs better than anything i've tried out there.
system.time(x<-readJPEG('~/Desktop/image.jpg'))
Takes about 1.431 seconds for a 4mb image and returns a n x m x 3 matrix with each layer of the matrix being a color channel
I don't know why it's slow, but try using raster instead. You can plot the results of reading it in with image
require( raster )
im <- brick("~/Desktop/image.jpg")
image( im , y = 1 )
# Or for a rgb coloured image...
plotRGB( im , r=1 , g = 2 , b = 3 )
# To extract values of each layer
vals <- getValues( im )
# A quicker way to get the values would be to use the as.matrix method for rasters
vals <- as.matrix( im )
Raster might give you a warning about georeferencing, but it should work and it should be pretty darn quick.