Converting a numpy array to grayscale

[Brickle Macho]

I porting a 8 line Matlab script. Basically I read in am image, down
sample the image, perform some FFT operations and output a final
smoothed image. I am porting this to a standalone function. The
problem is that I am getting different from my python script to what
Matlab was outputs

After comparing the contents of the array/matrix in python/matlab I
noticed the values were different after the image was converted to
grayscale. That is, when the image is read in, the values are the same,
once converted they begin to differ around the first/second decimal place.

If I read in the file using ndimage.imread( flatten=true) then I get the
same value as matlab correct to 5 decimal places, whereas using
color.rgb2gray() is only correct to 2 decimal places. In the final
version of the code I will only have access to the numpy array after it
has been loaded into memory, so using imread() was just for
tracing/locating/identifying the problem. Here is a snippet of code:

>>> gray = ndimage.imread('1.jpg',flatten=True)
>>> gray /= gray.max()
>>> gray
array([[ 0.30133331, 0.2895686 , 0.28172547, ...
...

>>> gray2 = color.rgb2gray(rgb)
>>> gray2
array([[ 0.31065608, 0.29889137, 0.29104824, ...,
...

I believe this difference is causing the problem. Note if I convert the
image to grayscale using a external tool and read this in then the
values of the numpy array match similar/same to Matlab matrix.

So what is the difference between converting an array to gray scale
verse reading it in as grayscale? Have I done something wrong? Is
there another way to convert a numpy array to grayscale?

Any help appreciated.

Michael.
--

[Johannes Schönberger]

Hi,

Could you provide us with both the grayscale and RGB version of your image?

Johannes Schönberger

> --
> You received this message because you are subscribed to the Google Groups "scikit-image" group.
> To unsubscribe from this group and stop receiving emails from it, send an email to scikit-image...@googlegroups.com.
> For more options, visit https://groups.google.com/groups/opt_out.
>
>

[Tony Yu]

On Fri, May 17, 2013 at 12:15 PM, Brickle Macho <brickl...@gmail.com> wrote:

I porting a 8 line Matlab script.  

<snip> 

So what is the difference between converting an array to gray scale verse reading it in as grayscale?  Have I done something wrong?  Is there another way to convert a numpy array to grayscale?

Any help appreciated.

Michael.
--

 

Hi Michael,

They're just different color conversion factors. Based on http://www.mathworks.com/help/images/ref/rgb2gray.html, Matlab uses:

0.2989 R + 0.5870 G + 0.1140 B 

Based on the docstring for `color.rgb2gray`:

0.2125 R + 0.7154 G + 0.0721 B

Wikipedia (http://en.wikipedia.org/wiki/Grayscale) seems to suggest that Matlab's is an older standard while the one in scikit-image is a more recent spec. 

[Brickle Macho]

On 18/05/13 1:19 AM, Johannes Sch�nberger wrote:
> Hi,
>
> Could you provide us with both the grayscale and RGB version of your image?

Sure. Here is a link to the images:

[1] http://i.imgur.com/jxBoL93.jpg
[2] http://i.imgur.com/q5jFcgL.jpg

Regards,

Michel.
--

[Brickle Macho]

Hi tony,

Thanks.  I suspect then that ndimage.imread(, flatten=True) is using the older standard, hence why the image values appeared the same. For testing purposes, I will use Matlab's conversion factor to see if I get the same output as the paper.  Once I am happy it is the same, then I will go back to using color.rgb2gray.

Thanks for your help.


Michael.
--