How can I prevent Numpy/ SciPy gaussian blur from converting image to grey scale?

Question

I want to perform gaussian blur on an image but I don't want to be convert to grey scale. Is there anyway to perform this operation and keep the color?

from scipy import misc

import scipy

import numpy as np

a = misc.imread('A.jpg')

# A retains its color
misc.imsave('color.jpg', a)

# A_G_Blur gets converted to grey scale, I want to prevent this
a_g_blure = ndimage.uniform_filter(a, size=11)

# I want it to keep it's color
misc.imsave('now_grey.jpg', a)

Answer 1

a is a 3-d array with shape (M, N, 3). The problem is that ndimage.uniform_filter(a, size=11) applies a filter with length 11 to each dimension of a, include the third axis that holds the color channels. When you apply the filter with length 11 to an axis with length 3, the resulting values are all pretty close to the average of the three values, so you get something pretty close to a gray scale. (Depending on the image, you might have some color left.)

What you actually want is to apply a 2-d filter to each color channel separately. You can do this by giving a tuple as the size argument, using a size of 1 for the last axis:

a_g_blure = ndimage.uniform_filter(a, size=(11, 11, 1))

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Note: uniform_filter is not a Gaussian blur. For that, you would use scipy.ndimage.gaussian_filter. You might also be interested in the filters provided by scikit-image. In particular, see skimage.filters.gaussian_filter.