Low rank approximation for the lena image

gistfile1.py

"""
Low rank approximation for the lena image
"""
import numpy as np
import scipy as sp
from scipy import linalg
import pylab as pl

X = sp.lena().astype(np.float)
pl.gray()
pl.imshow(X)
pl.show()

U, d, Vt = linalg.svd(X)
D = linalg.diagsvd(d, X.shape[0], X.shape[1])

# approxmation with some singular values set to zero
# we set half of them to zero

for k in range(5, 50, 3):
    D1 = D.copy()
    D1[D1 < d[int(k)]] = 0.
    print int(k)
    X1 = np.dot(np.dot(U, D1), Vt)
    pl.imshow(X1)
    pl.show()

Very nice example.