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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.

Este ejercicio forma parte del curso

Biomedical Image Analysis in Python

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Instrucciones del ejercicio

  • 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.

Ejercicio interactivo práctico

Prueba este ejercicio y completa el código de muestra.

# 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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