%matplotlib inline

Smooth an image

This example shows how to use squidpy.im.process to smooth an image layer of squidpy.im.ImageContainer().

We use the argument method="smooth" to smooth the image. This calls skimage.filters.gaussian in the background. Keyword arguments kwargs are passed to the wrapped function. This allows us to set the width of the Gaussian kernel, \(\\sigma\), used for smoothing.

See also

• Convert to grayscale.

• Process a high-resolution image.

import matplotlib.pyplot as plt

import squidpy as sq

# load the H&E stained tissue image
img = sq.datasets.visium_hne_image_crop()

Smooth the image with sigma = 2. With the argument layer we can select the image layer that should be processed. By default, the resulting image is saved in the layer image_smooth. This behavior can be changed with the arguments copy and layer_added.

sq.im.process(img, layer="image", method="smooth", sigma=2)

Now we can look at the result on a cropped part of the image.

crop = img.crop_corner(0, 0, size=200)

fig, axes = plt.subplots(1, 2)
for i, layer in enumerate(["image", "image_smooth"]):
    crop.show(layer, ax=axes[i])
    axes[i].set_title(layer)