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DOC: Minor clean-ups of equalization demo.

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Stefan van der Walt
2012-11-27 16:26:47 -08:00
parent 9adae8b0c2
commit 530fbbb2fc
1 changed files with 11 additions and 8 deletions
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doc/examples/plot_equalize.py
+11 -8
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@@ -18,7 +18,7 @@ that fall within the 2nd and 98th percentiles [2]_.
"""
from skimage import data, img_as_ubyte
from skimage import data, img_as_float
from skimage.util.dtype import dtype_range
from skimage import exposure
@@ -30,6 +30,7 @@ def plot_img_and_hist(img, axes, bins=256):
"""Plot an image along with its histogram and cumulative histogram.
"""
img = img_as_float(img)
ax_img, ax_hist = axes
ax_cdf = ax_hist.twinx()
@@ -38,16 +39,16 @@ def plot_img_and_hist(img, axes, bins=256):
ax_img.set_axis_off()
# Display histogram
ax_hist.hist(img.ravel(), bins=bins, histtype='stepfilled')
ax_hist.hist(img.ravel(), bins=bins, histtype='step', color='black')
ax_hist.ticklabel_format(axis='y', style='scientific', scilimits=(0, 0))
ax_hist.set_xlabel('Pixel intensity')
xmin, xmax = dtype_range[img.dtype.type]
ax_hist.set_xlim(xmin, xmax)
ax_hist.set_xlim(0, 1)
ax_hist.set_yticks([])
# Display cumulative distribution
img_cdf, bins = exposure.cumulative_distribution(img, bins)
ax_cdf.plot(bins, img_cdf, 'r')
ax_cdf.set_yticks([])
return ax_img, ax_hist, ax_cdf
@@ -62,29 +63,31 @@ img_rescale = exposure.rescale_intensity(img, in_range=(p2, p98))
# Equalization
img_eq = exposure.equalize_hist(img)
img_eq = img_as_ubyte(img_eq)
# Adaptive Equalization
img_adapteq = exposure.equalize_adapthist(img, clip_limit=0.03)
img_adapteq = img_as_ubyte(img_adapteq)
# Display results
f, axes = plt.subplots(2, 4, figsize=(8, 4))
ax_img, ax_hist, ax_cdf = plot_img_and_hist(img, axes[:, 0])
ax_img.set_title('Low contrast image')
y_min, y_max = ax_hist.get_ylim()
ax_hist.set_ylabel('Number of pixels')
ax_hist.set_yticks(np.linspace(0, y_max, 5))
ax_img, ax_hist, ax_cdf = plot_img_and_hist(img_rescale, axes[:, 1])
ax_img.set_title('Contrast stretching')
ax_img, ax_hist, ax_cdf = plot_img_and_hist(img_eq, axes[:, 2])
ax_img.set_title('Histogram equalization')
ax_cdf.set_ylabel('Fraction of total intensity')
ax_img, ax_hist, ax_cdf = plot_img_and_hist(img_adapteq, axes[:, 3])
ax_img.set_title('Adaptive equalization')
ax_cdf.set_ylabel('Fraction of total intensity')
ax_cdf.set_yticks(np.linspace(0, 1, 5))
# prevent overlap of y-axis labels
plt.subplots_adjust(wspace=0.4)