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You're reading from  Hands-On Image Processing with Python

Product typeBook
Published inNov 2018
Reading LevelIntermediate
PublisherPackt
ISBN-139781789343731
Edition1st Edition
Languages
Python
Tools
Keras
Concepts
Computer Vision
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Author (1)
Sandipan Dey
Sandipan Dey
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Sandipan Dey

Sandipan Dey is a data scientist with a wide range of interests, covering topics such as machine learning, deep learning, image processing, and computer vision. He has worked in numerous data science fields, working with recommender systems, predictive models for the events industry, sensor localization models, sentiment analysis, and device prognostics. He earned his master's degree in computer science from the University of Maryland, Baltimore County, and has published in a few IEEE Data Mining conferences and journals. He has earned certifications from 100+ MOOCs on data science, machine learning, deep learning, image processing, and related courses. He is a regular blogger (sandipanweb) and is a machine learning education enthusiast.
Read more about Sandipan Dey

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Questions

  1. Implement histogram matching for colored RGB images.
  2. Use the equalize()function from skimage.filters.rank to implement local histogram equalization and compare it with the global histogram equalization from skimage.exposure with a grayscale image.
  3. Implement Floyd-Steinberg error-diffusion dithering using the algorithm described here https://en.wikipedia.org/wiki/Floyd%E2%80%93Steinberg_ditheringand convert a grayscale image into a binary image.
  4. Use ModeFilter() from PIL for linear smoothing with an image. When is it useful?
  5. Show an image that can be recovered from a few noisy images obtained by adding random Gaussian noise to the original image by simply taking the average of the noisy images. Does taking the median also work?
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Hands-On Image Processing with Python
Published in: Nov 2018Publisher: PacktISBN-13: 9781789343731
© 2018 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Sandipan Dey

Sandipan Dey is a data scientist with a wide range of interests, covering topics such as machine learning, deep learning, image processing, and computer vision. He has worked in numerous data science fields, working with recommender systems, predictive models for the events industry, sensor localization models, sentiment analysis, and device prognostics. He earned his master's degree in computer science from the University of Maryland, Baltimore County, and has published in a few IEEE Data Mining conferences and journals. He has earned certifications from 100+ MOOCs on data science, machine learning, deep learning, image processing, and related courses. He is a regular blogger (sandipanweb) and is a machine learning education enthusiast.
Read more about Sandipan Dey

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