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tests_ch04.py
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tests_ch04.py
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import math
import os
import matplotlib.pyplot as plt
from skimage import io
import frequency_filters as ff
import spatial_filters as sf
def test_shrink_image(dirname, filename):
filename = os.path.join(dirname, filename)
image = io.imread(filename)
fig = plt.figure("Border detection")
ax = fig.add_subplot(1, 2, 1)
ax.set_title("Original Image")
plt.imshow(image, cmap="gray")
ax = fig.add_subplot(1, 2, 2)
ax.set_title("Shrinked Image")
shrink = ff.shrink_image(image, 2)
plt.imshow(shrink, cmap="gray")
plt.show()
def test_shrink_average_image(dirname, filename):
filename = os.path.join(dirname, filename)
image = io.imread(filename)
fig = plt.figure("Border detection")
ax = fig.add_subplot(1, 2, 1)
ax.set_title("Original Image")
plt.imshow(image, cmap="gray")
ax = fig.add_subplot(1, 2, 2)
ax.set_title("Shrinked Image")
shrink = ff.shrink_average_image(image, 2)
plt.imshow(shrink, cmap="gray")
plt.show()
def test_compute_spectrum(dirname, filename):
filename = os.path.join(dirname, filename)
image = io.imread(filename)
fig = plt.figure("Border detection")
ax = fig.add_subplot(1, 2, 1)
ax.set_title("Original Image")
plt.imshow(image, cmap="gray")
ax = fig.add_subplot(1, 2, 2)
ax.set_title("Spectrum")
spectrum = ff.compute_spectrum(image)
sf.log_transform(spectrum)
plt.imshow(spectrum, cmap="gray")
plt.show()
def test_low_pass_ideal_filter(dirname, filename):
filename = os.path.join(dirname, filename)
image = io.imread(filename)
fig = plt.figure("Frequency Filters")
ax = fig.add_subplot(1, 2, 1)
ax.set_title("Original Image")
plt.imshow(image, cmap="gray")
ax = fig.add_subplot(1, 2, 2)
ax.set_title("Ideal lowpass")
d0 = 60
func = lambda duv, d0=d0: 1 if duv <= d0 else 0
spectrum = ff.general_frequency_filter(image, func)
plt.imshow(spectrum, cmap="gray")
plt.show()
def test_low_pass_butterworth_filter(dirname, filename):
filename = os.path.join(dirname, filename)
image = io.imread(filename)
fig = plt.figure("Frequency Filters")
ax = fig.add_subplot(1, 2, 1)
ax.set_title("Original Image")
plt.imshow(image, cmap="gray")
ax = fig.add_subplot(1, 2, 2)
ax.set_title("Butterworth lowpass")
d0 = 60
n = 1
func = lambda duv, d0=d0, n=n: 1 / (1 + (duv / d0)**(2*n))
spectrum = ff.general_frequency_filter(image, func)
plt.imshow(spectrum, cmap="gray")
plt.show()
def test_low_pass_gaussian_filter(dirname, filename):
filename = os.path.join(dirname, filename)
image = io.imread(filename)
fig = plt.figure("Frequency Filters")
ax = fig.add_subplot(1, 2, 1)
ax.set_title("Original Image")
plt.imshow(image, cmap="gray")
ax = fig.add_subplot(1, 2, 2)
ax.set_title("Gaussian lowpass")
d0 = 60
func = lambda duv, d0=d0: math.exp(-(duv**2)/(2*(d0**2)))
spectrum = ff.general_frequency_filter(image, func)
plt.imshow(spectrum, cmap="gray")
plt.show()
def test_high_pass_ideal_filter(dirname, filename):
filename = os.path.join(dirname, filename)
image = io.imread(filename)
fig = plt.figure("Frequency Filters")
ax = fig.add_subplot(1, 2, 1)
ax.set_title("Original Image")
plt.imshow(image, cmap="gray")
ax = fig.add_subplot(1, 2, 2)
ax.set_title("Ideal Highpass")
d0 = 60
func = lambda duv, d0=d0: 0 if duv <= d0 else 1
spectrum = ff.general_frequency_filter(image, func)
plt.imshow(spectrum, cmap="gray")
plt.show()
def test_high_pass_butterworth_filter(dirname, filename):
filename = os.path.join(dirname, filename)
image = io.imread(filename)
fig = plt.figure("Border detection")
ax = fig.add_subplot(1, 2, 1)
ax.set_title("Original Image")
plt.imshow(image, cmap="gray")
ax = fig.add_subplot(1, 2, 2)
ax.set_title("Butterworth highpass")
d0 = 60
n = 1
func = lambda duv, d0=d0, n=n: 1 / (1 + (d0 / duv)**(2*n)) if duv != 0 else duv
spectrum = ff.general_frequency_filter(image, func)
plt.imshow(spectrum, cmap="gray")
plt.show()
def test_high_pass_gaussian_filter(dirname, filename):
filename = os.path.join(dirname, filename)
image = io.imread(filename)
fig = plt.figure("Border detection")
ax = fig.add_subplot(1, 2, 1)
ax.set_title("Original Image")
plt.imshow(image, cmap="gray")
ax = fig.add_subplot(1, 2, 2)
ax.set_title("Gaussian highpass")
d0 = 60
func = lambda duv, d0=d0: 1 - math.exp(-(duv**2)/(2*(d0**2)))
spectrum = ff.general_frequency_filter(image, func)
plt.imshow(spectrum, cmap="gray")
plt.show()
def test_bandreject_ideal_filter(dirname, filename):
filename = os.path.join(dirname, filename)
image = io.imread(filename)
fig = plt.figure("Frequency Filters")
ax = fig.add_subplot(1, 2, 1)
ax.set_title("Original Image")
plt.imshow(image, cmap="gray")
ax = fig.add_subplot(1, 2, 2)
ax.set_title("Ideal Bandreject")
d0 = 60
W = 20
func = lambda duv, d0=d0: 0 if duv <= (d0 - W/2) and duv <= (d0 + W/2) else 1
spectrum = ff.general_frequency_filter(image, func)
plt.imshow(spectrum, cmap="gray")
plt.show()
def test_bandreject_butterworth_filter(dirname, filename):
filename = os.path.join(dirname, filename)
image = io.imread(filename)
fig = plt.figure("Border detection")
ax = fig.add_subplot(1, 2, 1)
ax.set_title("Original Image")
plt.imshow(image, cmap="gray")
ax = fig.add_subplot(1, 2, 2)
ax.set_title("Butterworth highpass")
d0 = 60
n = 1
W = 20
func = lambda duv, d0=d0, n=n: 1 / (1 + ((duv*W) / ((duv**2) - (d0**2)))**(2*n)) \
if ((duv**2) - (d0**2)) != 0 else duv
spectrum = ff.general_frequency_filter(image, func)
plt.imshow(spectrum, cmap="gray")
plt.show()
def test_bandreject_gaussian_filter(dirname, filename):
filename = os.path.join(dirname, filename)
image = io.imread(filename)
fig = plt.figure("Frequency Filters")
ax = fig.add_subplot(1, 2, 1)
ax.set_title("Original Image")
plt.imshow(image, cmap="gray")
ax = fig.add_subplot(1, 2, 2)
ax.set_title("Gaussian bandreject")
d0 = 60
W = 10
func = lambda duv, d0=d0: 1 - math.exp(-(duv**2 - d0**2)/(duv*W)) if duv != 0 else duv
spectrum = ff.general_frequency_filter(image, func)
plt.imshow(spectrum, cmap="gray")
plt.show()
def test_bandpass_ideal_filter(dirname, filename):
filename = os.path.join(dirname, filename)
image = io.imread(filename)
fig = plt.figure("Frequency Filters")
ax = fig.add_subplot(1, 2, 1)
ax.set_title("Original Image")
plt.imshow(image, cmap="gray")
ax = fig.add_subplot(1, 2, 2)
ax.set_title("Ideal Bandpass")
d0 = 60
W = 20
func = lambda duv, d0=d0: 1 if duv <= (d0 - W/2) and duv <= (d0 + W/2) else 0
spectrum = ff.general_frequency_filter(image, func)
plt.imshow(spectrum, cmap="gray")
plt.show()
def test_bandpass_butterworth_filter(dirname, filename):
filename = os.path.join(dirname, filename)
image = io.imread(filename)
fig = plt.figure("Border detection")
ax = fig.add_subplot(1, 2, 1)
ax.set_title("Original Image")
plt.imshow(image, cmap="gray")
ax = fig.add_subplot(1, 2, 2)
ax.set_title("Butterworth Bandpass")
d0 = 60
n = 1
W = 20
func = lambda duv, d0=d0, n=n: 1 - (1 / (1 + ((duv*W) / ((duv**2) - (d0**2)))**(2*n))) \
if ((duv**2) - (d0**2)) != 0 else duv
spectrum = ff.general_frequency_filter(image, func)
plt.imshow(spectrum, cmap="gray")
plt.show()
def test_bandpass_gaussian_filter(dirname, filename):
filename = os.path.join(dirname, filename)
image = io.imread(filename)
fig = plt.figure("Frequency Filters")
ax = fig.add_subplot(1, 2, 1)
ax.set_title("Original Image")
plt.imshow(image, cmap="gray")
ax = fig.add_subplot(1, 2, 2)
ax.set_title("Gaussian bandreject")
d0 = 60
W = 10
func = lambda duv, d0=d0: math.exp(-(duv**2 - d0**2)/(duv*W)) if duv != 0 else duv
spectrum = ff.general_frequency_filter(image, func)
plt.imshow(spectrum, cmap="gray")
plt.show()
def test_batch_CH04():
dir_name = "C:\\Users\\MarcosFelipe\\Documents\\PhotoTops\\DIP3E_CH04"
# test_shrink_image(dir_name, "Fig0417(a)(barbara).tif")
# test_shrink_average_image(dir_name, "Fig0417(a)(barbara).tif")
test_compute_spectrum(dir_name, "Fig0424(a)(rectangle).tif")
test_compute_spectrum(dir_name, "Fig0427(a)(woman).tif")
# test_low_pass_ideal_filter(dir_name, "Fig0441(a)(characters_test_pattern).tif")
# test_low_pass_butterworth_filter(dir_name, "Fig0441(a)(characters_test_pattern).tif")
# test_low_pass_gaussian_filter(dir_name, "Fig0441(a)(characters_test_pattern).tif")
# test_high_pass_ideal_filter(dir_name, "Fig0441(a)(characters_test_pattern).tif")
# test_high_pass_butterworth_filter(dir_name, "Fig0441(a)(characters_test_pattern).tif")
# test_high_pass_gaussian_filter(dir_name, "Fig0441(a)(characters_test_pattern).tif")
# test_bandreject_ideal_filter(dir_name, "Fig0462(a)(PET_image).tif")
# test_bandreject_butterworth_filter(dir_name, "Fig0462(a)(PET_image).tif")
# test_bandreject_gaussian_filter(dir_name, "Fig0462(a)(PET_image).tif")
# test_bandpass_ideal_filter(dir_name, "Fig0462(a)(PET_image).tif")
# test_bandpass_butterworth_filter(dir_name, "Fig0462(a)(PET_image).tif")
# test_bandpass_gaussian_filter(dir_name, "Fig0462(a)(PET_image).tif")