Decoration to the rescue!

import numpy as np
from scipy import signal
from opencv import adaptors


class scipyFromOpenCV(object):
    """This decorator can be used to wrap a function that takes 
    and returns a numpy array into one that takes and retuns an
    opencv CvMat.
    """
    def __init__(self, f):
        self.f = f    

    def __call__(self, image):
        # Convert CvMat to ndarray
        np_image = adaptors.Ipl2NumPy(image)
        
        # Call the original function
        np_image_filtered = self.f(np_image)
        
        # Convert back to CvMat
        return adaptors.NumPy2Ipl(np_image_filtered)

@scipyFromOpenCV
def slowGaussianBlur(matrix):
    """Manual gaussian blur - Very very very slow!"""
    filterSize = 3
    filt = gauss_kern(filterSize)

    r = signal.convolve(matrix[:,:,0],filt,'same')
    g = signal.convolve(matrix[:,:,1],filt,'same')
    b = signal.convolve(matrix[:,:,2],filt,'same')
    
    result = array([r,b,g]).astype(uint8).transpose((1,2,0))
   
    return result