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Resampling

Images can be collected in a variety of shapes and sizes. Resampling is a useful tool when these shapes need to be made consistent. Two common applications are:

  • Downsampling: combining pixel data to decrease size
  • Upsampling: distributing pixel data to increase size

For this exercise, transform and then resample the brain image (im) to see how it affects image shape.

Diese Übung ist Teil des Kurses

<Kurs>Biomedical Image Analysis in Python</Kurs>
Kurs ansehen

Übungsanweisungen

  • Shift im 20 pixels left and 20 pixels up, i.e. (-20, -20). Then, rotate it 35 degrees downward. Remember to specify a value for reshape.
  • Use ndi.zoom() to downsample the image from (256, 256) to (64, 64).
  • Use ndi.zoom() to upsample the image from (256, 256) to (1024, 1024).
  • Plot the resampled images.

Interaktive praktische Übung

Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.

# Center and level image
xfm = ndi.shift(____, shift=____)
xfm = ndi.rotate(____, angle=____, reshape=____)

# Resample image
im_dn = ndi.zoom(xfm, zoom=____)
im_up = ____

# Plot the images
fig, axes = plt.subplots(2, 1)
axes[0].imshow(im_dn)
____
format_and_render_plot()
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