Python Image Processing Cookbook

How it works...

We started by applying the mean filter to the noisy images with the uniform_filter() function from the scipy.ndimage module. Then, we applied the median filter to the noisy images with median_filer() from the same module. For both the filters, the filter size used was 5, in order to apply a 5 x 5 convolution with the box kernel.

The compare_psnr() function from the skimage.measure module was used to compare the quality of the images denoised using the filters.

The imread() function from the scikit-image.io module was used to read the Lena RGB image and the rgb2gray() function from the scikit-image.color module was used to convert the image to grayscale.

We used either the random_noise() function from the scikit-image.util ...