# Lowpass then Inverse filtering in python

I wrote a simple lowpass filter in python to run against lena. Now I'd like to add Gaussian noise to the lowpass filtered data and then run an inverse filter against the lowpass and try to get the original back (well, as close to original). I'm new to programming in python and not quite sure how to add noise and write the inverse.

import matplotlib.pyplot as plt
import numpy as np
import scipy.misc
from scipy import ndimage
import Image

def plot(data, title):
plot.i += 1
plt.subplot(2,2,plot.i)
plt.imshow(data)
plt.gray()
plt.title(title)
plot.i = 0