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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 exercício faz parte do curso

Biomedical Image Analysis in Python

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Instruções do exercício

  • 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.

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

# 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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