def test_daubechies_idaubechies():
f = luispedro_jpg(1)
f = f[:256,:256]
fo = f.copy()
d = mahotas.daubechies(f, 'D8')
r = mahotas.idaubechies(d, 'D8')
assert np.mean( (r[4:-4,4:-4] - fo[4:-4,4:-4])**2) < 1.
def test_daubechies_idaubechies():
f = luispedro_jpg()
f = f[:256, :256]
fo = f.copy()
d = mahotas.daubechies(f, 'D8')
r = mahotas.idaubechies(d, 'D8')
assert np.mean((r[4:-4, 4:-4] - fo[4:-4, 4:-4])**2) < 1.
def test_center_wavelet_iwavelet_decenter():
from mahotas import wavelet_center, wavelet_decenter
import mahotas
import numpy as np
f = luispedro_jpg(1)
f = f[:100,:250]
fo = f.copy()
for wav in ('D2', 'D4', 'D6', 'D8', 'D10', 'D12', 'D16'):
fc = mahotas.wavelet_center(fo, border=24)
t = mahotas.daubechies(fc, wav)
r = mahotas.idaubechies(t, wav)
rd = mahotas.wavelet_decenter(r, fo.shape, border=24)
assert np.allclose(fo, rd)
def test_center_wavelet_iwavelet_decenter():
from mahotas import wavelet_center, wavelet_decenter
import mahotas
import numpy as np
f = luispedro_jpg()
f = f[:100, :250]
fo = f.copy()
for wav in ('D2', 'D4', 'D6', 'D8', 'D10', 'D12', 'D16'):
fc = mahotas.wavelet_center(fo, border=24)
t = mahotas.daubechies(fc, wav)
r = mahotas.idaubechies(t, wav)
rd = mahotas.wavelet_decenter(r, fo.shape, border=24)
assert np.allclose(fo, rd)
direct = f[::2, ::2].copy()
direct /= 8
direct = direct.astype(np.uint8)
print("Fraction of zeros in original image (after division by 8):",
np.mean(direct == 0))
plt.imshow(direct)
# Transform using D8 Wavelet to obtain transformed image t:
t = mahotas.daubechies(f, 'D8')
plt.imshow(t)
# Discard low-order bits:
t /= 8
t = t.astype(np.int8)
print("Fraction of zeros in transform (after division by 8):", np.mean(t == 0))
plt.imshow(t)
# Let us look at what this looks like
r = mahotas.idaubechies(t, 'D8')
plt.imshow(r)
# Go further, discard small values in the transformed space:
tt = soft_threshold(t, 12)
print(
"Fraction of zeros in transform (after division by 8 & soft thresholding):",
np.mean(tt == 0))
# Let us look again at what we have:
rt = mahotas.idaubechies(tt, 'D8')
plt.imshow(rt)
# A baseline compression method: save every other pixel and only high-order bits:
direct = f[::2,::2].copy()
direct /= 8
direct = direct.astype(np.uint8)
print("Fraction of zeros in original image (after division by 8):", np.mean(direct==0))
plt.imshow(direct)
# Transform using D8 Wavelet to obtain transformed image t:
t = mahotas.daubechies(f,'D8')
plt.imshow(t)
# Discard low-order bits:
t /= 8
t = t.astype(np.int8)
print("Fraction of zeros in transform (after division by 8):", np.mean(t==0))
plt.imshow(t)
# Let us look at what this looks like
r = mahotas.idaubechies(t, 'D8')
plt.imshow(r)
# Go further, discard small values in the transformed space:
tt = soft_threshold(t, 12)
print("Fraction of zeros in transform (after division by 8 & soft thresholding):", np.mean(tt==0))
# Let us look again at what we have:
rt = mahotas.idaubechies(tt, 'D8')
plt.imshow(rt)
