.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/color_exposure/plot_local_equalize.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code or to run this example in your browser via Binder .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_color_exposure_plot_local_equalize.py: ============================ Local Histogram Equalization ============================ This example enhances an image with low contrast, using a method called *local histogram equalization*, which spreads out the most frequent intensity values in an image. The equalized image [1]_ has a roughly linear cumulative distribution function for each pixel neighborhood. The local version [2]_ of the histogram equalization emphasized every local graylevel variations. These algorithms can be used on both 2D and 3D images. References ---------- .. [1] https://en.wikipedia.org/wiki/Histogram_equalization .. [2] https://en.wikipedia.org/wiki/Adaptive_histogram_equalization .. GENERATED FROM PYTHON SOURCE LINES 24-102 .. code-block:: Python import numpy as np import matplotlib import matplotlib.pyplot as plt from skimage import data from skimage.util.dtype import dtype_range from skimage.util import img_as_ubyte from skimage import exposure from skimage.morphology import disk from skimage.morphology import ball from skimage.filters import rank matplotlib.rcParams['font.size'] = 9 def plot_img_and_hist(image, axes, bins=256): """Plot an image along with its histogram and cumulative histogram.""" ax_img, ax_hist = axes ax_cdf = ax_hist.twinx() # Display image ax_img.imshow(image, cmap=plt.cm.gray) ax_img.set_axis_off() # Display histogram ax_hist.hist(image.ravel(), bins=bins) ax_hist.ticklabel_format(axis='y', style='scientific', scilimits=(0, 0)) ax_hist.set_xlabel('Pixel intensity') xmin, xmax = dtype_range[image.dtype.type] ax_hist.set_xlim(xmin, xmax) # Display cumulative distribution img_cdf, bins = exposure.cumulative_distribution(image, bins) ax_cdf.plot(bins, img_cdf, 'r') return ax_img, ax_hist, ax_cdf # Load an example image img = img_as_ubyte(data.moon()) # Global equalize img_rescale = exposure.equalize_hist(img) # Equalization footprint = disk(30) img_eq = rank.equalize(img, footprint=footprint) # Display results fig = plt.figure(figsize=(8, 5)) axes = np.zeros((2, 3), dtype=object) axes[0, 0] = plt.subplot(2, 3, 1) axes[0, 1] = plt.subplot(2, 3, 2, sharex=axes[0, 0], sharey=axes[0, 0]) axes[0, 2] = plt.subplot(2, 3, 3, sharex=axes[0, 0], sharey=axes[0, 0]) axes[1, 0] = plt.subplot(2, 3, 4) axes[1, 1] = plt.subplot(2, 3, 5) axes[1, 2] = plt.subplot(2, 3, 6) ax_img, ax_hist, ax_cdf = plot_img_and_hist(img, axes[:, 0]) ax_img.set_title('Low contrast image') ax_hist.set_ylabel('Number of pixels') ax_img, ax_hist, ax_cdf = plot_img_and_hist(img_rescale, axes[:, 1]) ax_img.set_title('Global equalise') ax_img, ax_hist, ax_cdf = plot_img_and_hist(img_eq, axes[:, 2]) ax_img.set_title('Local equalize') ax_cdf.set_ylabel('Fraction of total intensity') # prevent overlap of y-axis labels fig.tight_layout() .. image-sg:: /auto_examples/color_exposure/images/sphx_glr_plot_local_equalize_001.png :alt: Low contrast image, Global equalise, Local equalize :srcset: /auto_examples/color_exposure/images/sphx_glr_plot_local_equalize_001.png :class: sphx-glr-single-img .. GENERATED FROM PYTHON SOURCE LINES 103-109 3D Equalization =============== 3D Volumes can also be equalized in a similar fashion. Here the histograms are collected from the entire 3D image, but only a single slice is shown for visual inspection. .. GENERATED FROM PYTHON SOURCE LINES 110-169 .. code-block:: Python matplotlib.rcParams['font.size'] = 9 def plot_img_and_hist(image, axes, bins=256): """Plot an image along with its histogram and cumulative histogram.""" ax_img, ax_hist = axes ax_cdf = ax_hist.twinx() # Display Slice of Image ax_img.imshow(image[0], cmap=plt.cm.gray) ax_img.set_axis_off() # Display histogram ax_hist.hist(image.ravel(), bins=bins) ax_hist.ticklabel_format(axis='y', style='scientific', scilimits=(0, 0)) ax_hist.set_xlabel('Pixel intensity') xmin, xmax = dtype_range[image.dtype.type] ax_hist.set_xlim(xmin, xmax) # Display cumulative distribution img_cdf, bins = exposure.cumulative_distribution(image, bins) ax_cdf.plot(bins, img_cdf, 'r') return ax_img, ax_hist, ax_cdf # Load an example image img = img_as_ubyte(data.brain()) # Global equalization img_rescale = exposure.equalize_hist(img) # Local equalization neighborhood = ball(3) img_eq = rank.equalize(img, footprint=neighborhood) # Display results fig, axes = plt.subplots(2, 3, figsize=(8, 5)) axes[0, 1] = plt.subplot(2, 3, 2, sharex=axes[0, 0], sharey=axes[0, 0]) axes[0, 2] = plt.subplot(2, 3, 3, sharex=axes[0, 0], sharey=axes[0, 0]) ax_img, ax_hist, ax_cdf = plot_img_and_hist(img, axes[:, 0]) ax_img.set_title('Low contrast image') ax_hist.set_ylabel('Number of pixels') ax_img, ax_hist, ax_cdf = plot_img_and_hist(img_rescale, axes[:, 1]) ax_img.set_title('Global equalize') ax_img, ax_hist, ax_cdf = plot_img_and_hist(img_eq, axes[:, 2]) ax_img.set_title('Local equalize') ax_cdf.set_ylabel('Fraction of total intensity') # prevent overlap of y-axis labels fig.tight_layout() plt.show() .. image-sg:: /auto_examples/color_exposure/images/sphx_glr_plot_local_equalize_002.png :alt: Low contrast image, Global equalize, Local equalize :srcset: /auto_examples/color_exposure/images/sphx_glr_plot_local_equalize_002.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 3.089 seconds) .. _sphx_glr_download_auto_examples_color_exposure_plot_local_equalize.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: binder-badge .. image:: images/binder_badge_logo.svg :target: https://mybinder.org/v2/gh/scikit-image/scikit-image/v0.23.2?filepath=notebooks/auto_examples/color_exposure/plot_local_equalize.ipynb :alt: Launch binder :width: 150 px .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_local_equalize.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_local_equalize.py ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_