Noise

Image Processing in Python

Rebeca Gonzalez

Data Engineer

Noise

Apply noise in scikit-image

# Import the module and function
from skimage.util import random_noise


# Add noise to the image
noisy_image = random_noise(dog_image)


# Show original and resulting image
show_image(dog_image)
show_image(noisy_image, 'Noisy image')

Apply noise in scikit-image

Reducing noise

Denoising types

Total variation (TV)
Bilateral
Wavelet denoising
Non-local means denoising

Denoising

Using total variation filter denoising

from skimage.restoration import denoise_tv_chambolle


# Apply total variation filter denoising
denoised_image = denoise_tv_chambolle(noisy_image, 
                                      weight=0.1,
                                      multichannel=True)


# Show denoised image
show_image(noisy_image, 'Noisy image')
show_image(denoised_image, 'Denoised image')

Denoising

Total variation filter

Denoising

Bilateral filter

from skimage.restoration import denoise_bilateral


# Apply bilateral filter denoising
denoised_image = denoise_bilateral(noisy_image, multichannel=True)


# Show original and resulting images
show_image(noisy_image, 'Noisy image')
show_image(denoised_image, 'Denoised image')

Denoising

Bilateral filter

Let's practice!

Image Processing in Python