The right way to access red channel in Lena

[Adam Hughes]

I'm trying to build a filter to show only the red channel in the lena image.  I defined two masks:

(1,0,0)

(255,0,0)

Oddly, the (255,0,0) gives me the correct plot when doing imshow(), but (1,0,0) doesn't.  Why does the (1,0,0) mask lead to light regions being dark and dark regions being light?  Here's a working example:

%pylab inline

from skimage.data import lena

lena = lena()

f, (ax1, ax2) = plt.subplots(1,2, figsize=(8,6))

ax1.imshow(lena*(1,0,0))

ax2.imshow(lena*(255,0,0))

[Josh Warner]

Hi Adam,

You can slice out just the red channel with `lena[..., 0]`, which is equivalent to `lena[:, :, 0]`. The result will be a rank 2 array representing the red channel. This ability is made possible by NumPy.

[Adam Hughes]

I don't think the image came through.  Let me attach it

[Adam Hughes]

Thanks Josh.  I actually would normally do it that way, but I stumbled on this behavior when we were trying to build filters.  For example, scale the red channel by 50% via multiplying by (0.5, 1, 1).  Just curious what's going on, and why multiplcation by (1,0,0) doesn't work.

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[Stéfan van der Walt]

Hi Adam

On Thu, Mar 26, 2015 at 4:31 PM, Adam Hughes <hughes...@gmail.com> wrote:

ax1.imshow(lena*(1,0,0))

ax2.imshow(lena*(255,0,0))

The multiplication turns your image's dtype into uint64, which causes the scaling problems.

I prefer with float images, always ensuring that they are in [0, 1] and then specifying vmin=0 and vmax=1 to matplotlib.

Regards

Stéfan

[Adam Hughes]

Thanks!

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