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Python Image Processing Cookbook

You're reading from   Python Image Processing Cookbook Over 60 recipes to help you perform complex image processing and computer vision tasks with ease

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Product type Paperback
Published in Apr 2020
Publisher Packt
ISBN-13 9781789537147
Length 438 pages
Edition 1st Edition
Languages
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Author (1):
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Sandipan Dey Sandipan Dey
Author Profile Icon Sandipan Dey
Sandipan Dey
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Toc

Table of Contents (11) Chapters Close

Preface 1. Image Manipulation and Transformation 2. Image Enhancement FREE CHAPTER 3. Image Restoration 4. Binary Image Processing 5. Image Registration 6. Image Segmentation 7. Image Classification 8. Object Detection in Images 9. Face Recognition, Image Captioning, and More 10. Other Books You May Enjoy

Image restoration with a Markov random field

In this recipe, we shall discuss how a Markov random field (MRF) can be used to denoise an image. Let's say we have a noisy binary image, X, with pixel values Xij ∈ {-1, +1} and we want to recover the noiseless image, Y. If the amount of noise is assumed to be small, there will be a good correlation between a pixel in X and the corresponding pixel in Y and in a 4-connected neighborhood, pixels of X will be well-correlated. This can be modeled as an MRF as shown in the following diagram, with the total energy function that we shall like to minimize:

Getting ready

In this recipe, we will use the cameraman grayscale image and we will corrupt the image with noise. Next...

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