ImageMagick: Looking for a fast way to blur an image - perl

Question

I am searching for a faster way to blur an image than to use the GaussianBlur.
The solution I am looking for can be a command line solution, but I prefer code in perl notation.
Actually, we use the Perl image magick API to blur images:
# $image is our Perl object holding a imagemagick perl image
# level is a natural number between 1 and 10
$image->GaussianBlur('x' . $level);
This works fine, but with the level height the amount of time it consumes seems to grow exponentially.
Question: How can I improve the time used for the bluring operation?
Is there another faster approach to blur images?

Answer 1

I found that the suggested method of resizing image for blur imitation makes output look very pixelated for very large values of sigma like 25 or more. So I finally came to an idea of downscale-blur-enlarge, which makes very nice result (almost indistinguishable from simple blur with large sigma):
# plain slow blur
convert -blur 0x25 sample.jpg blurred_slow.jpg
# much faster
convert -scale 10% -blur 0x2.5 -resize 1000% sample.jpg blurred_fast.jpg
On my i5 2.7Ghz it shows up to 10x speed up.

Answer 2

The documentation speaks of the difference between Blur and GaussianBlur.
There has been some confusion as to which operator, "-blur" or the
"-gaussian-blur" is better for blurring images. First of all "-blur"
is faster, but it does this using two stage technique. First in one
axis, then in the other. The "-gaussian-blur" operator on the other
hand is more mathematically correct as it blurs in all directions
simultaneously. The speed cost between the two can be enormous, by a
factor of 10 or more, depending on the amount of bluring involved.
[...]
In summary, the two operators are slightly different, but only
minimally. As "-blur" is much faster, use it. I do in just about all
the examples involving blurring. Large
That would simply be:
$image->Blur( 'x' . $level );
But the Perl ImageMagick documentation has the same text on both Blur and GaussianBlur (emphasis mine). I can't try now, you would have to benchmark it yourself.
Blur: reduce image noise and reduce detail levels with a Gaussian operator of the given radius and standard deviation (sigma).
GaussianBlur: reduce image noise and reduce detail levels with a Gaussian operator of the given radius and standard deviation (sigma).
An alternative that the documentation also lists is resizing the image to be very tiny, and then enlarging again.
Using large sigma values for image bluring is very slow. But onw
technique can be used to speed up this process. This however is only a
rough method and could use some mathematicaly rigor to improve
results. Essentually the reason large blurs are slow is because you
need a large window or 'kernel' to merge lots of pixels together, for
each and every pixel in the image. However resize (making image
smaller) does the same thing but generates fewer pixels in the
process. The technique is basically shrink the image, then enlarge it
again to generate the heavilly blured result. The Gaussian Filter is
especially useful for this as you can directly specify a Gaussian
Sigma define.
The example command line code is this:
convert rose: -blur 0x5 rose_blur_5.png
convert rose: -filter Gaussian -resize 50% \
-define filter:sigma=2.5 -resize 200% rose_resize_5.png

Answer 3

Not sure if I could still help OP with this, but I recently tried the same for a blurred screenlock picture.
I found that omitting the -blur part saves even more calculation time and is still delivering great results for a 4K picture:
convert in.png -scale 2.5% -resize 4000% out.png
# real: 0.174s user: 0.144s size: 1.2MiB
convert in.png -scale 10% -blur 0x2.5 -resize 1000% out.png
# real: 0.136s user: 2.117s size: 1.2MiB
convert in.png -blur 0x25 out.png
# real: 2.425s user: 21.408s size: 1KiB
However, you couldn't go lower than 2.5% with 3840x2160. It will resize the image. I guess the eps value differs for pictures of other sizes.
It should be noted, that the resulting image sizes differ noticably!