def noise_filter(image, selem, out=None, mask=None, shift_x=False, shift_y=False):
 centre_r = (int((selem.shape[0] / 2)) + shift_y)
 centre_c = (int((selem.shape[1] / 2)) + shift_x)
 selem_cpy = selem.copy()
 selem_cpy[(centre_r, centre_c)] = 0
 return _apply_scalar_per_pixel(generic_cy._noise_filter, image, selem_cpy, out=out, mask=mask, shift_x=shift_x, shift_y=shift_y)

def noise_filter ( image , selem , out = None , mask = None , shift_x = False , shift_y = False ) : centre_r = ( int ( ( selem . shape [ 0 ] / 2 ) ) + shift_y ) centre_c = ( int ( ( selem . shape [ 1 ] / 2 ) ) + shift_x ) selem_cpy = selem . copy ( ) selem_cpy [ ( centre_r , centre_c ) ] = 0 return _apply_scalar_per_pixel ( generic_cy . _noise_filter , image , selem_cpy , out = out , mask = mask , shift_x = shift_x , shift_y = shift_y )
noise feature .