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.
This exercise is part of the course
Biomedical Image Analysis in Python
Exercise 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.
Hands-on interactive exercise
Have a go at this exercise by completing this sample 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()