Filters

Biomedical Image Analysis in Python

Stephen Bailey

Instructor

Filters

Examles of filtered images

Convolution with a sharpening filter

convolution-example

Convolution with a sharpening filter

convolution-result

By Michael Plotke - Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=24288958

Image convolution

import imageio
import scipy.ndimage as ndi

im=imageio.imread('foot-xray.jpg')

weights = [[.11,  .11, .11],
           [.11,  .12, .11],
           [.11,  .11, .11]]

im_filt = ndi.convolve(im, weights)

fig, axes = plt.subplots(2, 1)
axes[0].imshow(im, cmap='gray')
axes[1].imshow(im_filt,cmap='gray')
plt.imshow()

smoothed-foot-xray

Filtering functions

scipy.ndimage.filters includes:

median_filter()
uniform_filter()
maximum_filter()
percentile_filter()

ndi.median_filter(im, size=10)

foot-median

Gaussian filtering

Gaussian distribution in 1 dimension Gaussian distribution 1D

ndi.gaussian_filter(im, sigma=5)

Blur at sigma = 5

Gaussian distribution in 2 dimensions By Kghose at the English language Wikipedia, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=2550031

ndi.gaussian_filter(im, sigma=10)

Blur at sigma = 10

Let's practice!

Biomedical Image Analysis in Python