import numpy as np
from numpy.fft import fft2,ifft2,fftshift
import matplotlib.pyplot as plt
from scipy.misc import imread

img = imread('car.png',flatten=True)

img_fft = fft2(img)

# Hent terskler for slik at vi f?r ca like mange fft-koeffisienter i hver b?s [ikke et n?dvendig steg]
thresholds = [np.percentile(np.abs(img_fft), i) for i in np.linspace(0, 100, 15)]

plt.figure()
ind = 1
for thr in thresholds:
    img_thr = img_fft.copy()
    img_thr[np.abs(img_fft) < thr] = 0
    img_recon = ifft2(img_thr)
    #
    plt.subplot(7,4,ind)
    plt.imshow(np.log(np.abs(img_thr)+1),aspect='auto')
    #plt.imshow(np.log(np.abs(img_thr)+1),cmap='gray',aspect='auto')
    plt.title('Bevarte koeffsienter: %g %%'%(np.sum(img_thr != 0)*100.0/img.size))
    #
    plt.subplot(7,4,ind+1)
    plt.imshow(np.abs(img_recon),cmap='gray',aspect='auto')
    plt.title('Rekonstruert bilde ved terskel: %d'%thr)
    ind += 2

plt.show()