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.
Cet exercice fait partie du cours
Biomedical Image Analysis in Python
Instructions
- Shift
im20 pixels left and 20 pixels up, i.e.(-20, -20). Then, rotate it 35 degrees downward. Remember to specify a value forreshape. - 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.
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# 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()