I've got an image that I apply a Gaussian Blur to using both `cv2.GaussianBlur` and `skimage.gaussian_filter` libraries, but I get significantly different results. I'm curious as to why, and what can be done to make `skimage` look more like `cv2`. I know `skimage.gaussian_filter` is a wrapper around `scipy.scipy.ndimage.filters.gaussian_filter`. To clearly state the question, why are the two functions different and what can be done to make them more similar?

Here is my test image:

[![Original Image](https://i.stack.imgur.com/bg4dZ.png)](https://i.stack.imgur.com/bg4dZ.png)

Here is the `cv2` version (appears blurrier):

[![cv2 image](https://i.stack.imgur.com/zmVUu.png)](https://i.stack.imgur.com/zmVUu.png)

Here is the `skimage`/`scipy` version (appears sharper):

[![skimage version](https://i.stack.imgur.com/Tlmbr.png)](https://i.stack.imgur.com/Tlmbr.png)

Details:

`skimage_response = skimage.filters.gaussian_filter(im, 2, multichannel=True, mode='reflect')`

`cv2_response = cv2.GaussianBlur(im, (33, 33), 2)`

So sigma=2 and the size of the filter is big enough that it shouldn't make a difference. Imagemagick `covnert -gaussian-blur 0x2` visually agrees with `cv2`.

Versions: `cv2`=2.4.10, `skimage`=0.11.3, `scipy`=0.13.3