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IPython Interactive Computing and Visualization Cookbook - Second Edition by Cyrille Rossant

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Applying filters on an image

In this recipe, we apply filters on an image for various purposes: blurring, denoising, and edge detection.

How it works...

  1. Let's import the packages:
    >>> import numpy as np
        import matplotlib.pyplot as plt
        import skimage
        import skimage.color as skic
        import skimage.filters as skif
        import skimage.data as skid
        import skimage.util as sku
        %matplotlib inline
  2. We create a function that displays a grayscale image:
    >>> def show(img):
            fig, ax = plt.subplots(1, 1, figsize=(8, 8))
            ax.imshow(img, cmap=plt.cm.gray)
            ax.set_axis_off()
            plt.show()
  3. Now, we load the Astronaut image (bundled in scikit-image). We convert it to a grayscale image with the rgb2gray() function:
    >>> img = skic.rgb2gray(skid.astronaut())
    >>> show(img)
  4. Let's apply a blurring ...

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