Rescale, resize, and downscaleΒΆ

Rescale operation resizes an image by a given scaling factor. The scaling factor can either be a single floating point value, or multiple values - one along each axis.

Resize serves the same purpose, but allows to specify an output image shape instead of a scaling factor.

Note that when down-sampling an image, resize and rescale should perform Gaussian smoothing to avoid aliasing artifacts. See the anti_aliasing and anti_aliasing_sigma arguments to these functions.

Downscale serves the purpose of down-sampling an n-dimensional image by integer factors using the local mean on the elements of each block of the size factors given as a parameter to the function.

Original image, Rescaled image (aliasing), Resized image (no aliasing), Downscaled image (no aliasing)
import matplotlib.pyplot as plt

from skimage import data, color
from skimage.transform import rescale, resize, downscale_local_mean

image = color.rgb2gray(data.astronaut())

image_rescaled = rescale(image, 0.25, anti_aliasing=False)
image_resized = resize(image, (image.shape[0] // 4, image.shape[1] // 4),
                       anti_aliasing=True)
image_downscaled = downscale_local_mean(image, (4, 3))

fig, axes = plt.subplots(nrows=2, ncols=2)

ax = axes.ravel()

ax[0].imshow(image, cmap='gray')
ax[0].set_title("Original image")

ax[1].imshow(image_rescaled, cmap='gray')
ax[1].set_title("Rescaled image (aliasing)")

ax[2].imshow(image_resized, cmap='gray')
ax[2].set_title("Resized image (no aliasing)")

ax[3].imshow(image_downscaled, cmap='gray')
ax[3].set_title("Downscaled image (no aliasing)")

ax[0].set_xlim(0, 512)
ax[0].set_ylim(512, 0)
plt.tight_layout()
plt.show()

Total running time of the script: ( 0 minutes 0.539 seconds)

Gallery generated by Sphinx-Gallery