Implementation of the noise function

noise.py

def noise(image):
    """ Compute the noise feature.

    Parameters
    ----------
    image: ndarray
        Image array (uint8 array).

    Returns
    -------
    out: float
        The noise feature as described in [1]

    [1] N. Hashimoto et al. Referenceless image quality evaluation for whole slide imaging. J Pathol Inform 2012;3:9. 
    """
    # Define a sliding window
    sl = lambda i : slice(i-1, i+2)
    
    # Testing whether the image is RGB or not
    nc = lambda im : 3 if len(im.shape)==3 else 1

    # Don't use the center value
    idx = ([0, 0, 0, 1, 1, 2, 2, 2],
           [0, 1, 2, 0, 2, 0, 1, 2])

    height, width = image.shape[:2]
    d_square = np.zeros(nc(image))

    N = 0.

    for r in xrange(1, height-1):
        for c in xrange(1, width-1):
            # Making sure we can have negative values
            window = image[sl(r), sl(c)].astype(int)
            m = np.min(abs( window - window[1, 1])[idx], axis=0)
            d_square += m**2
            N += 1.

    return np.mean(d_square / N)