Book Image

Python Image Processing Cookbook

By : Sandipan Dey
Book Image

Python Image Processing Cookbook

By: Sandipan Dey

Overview of this book

With the advancements in wireless devices and mobile technology, there's increasing demand for people with digital image processing skills in order to extract useful information from the ever-growing volume of images. This book provides comprehensive coverage of the relevant tools and algorithms, and guides you through analysis and visualization for image processing. With the help of over 60 cutting-edge recipes, you'll address common challenges in image processing and learn how to perform complex tasks such as object detection, image segmentation, and image reconstruction using large hybrid datasets. Dedicated sections will also take you through implementing various image enhancement and image restoration techniques, such as cartooning, gradient blending, and sparse dictionary learning. As you advance, you'll get to grips with face morphing and image segmentation techniques. With an emphasis on practical solutions, this book will help you apply deep learning techniques such as transfer learning and fine-tuning to solve real-world problems. By the end of this book, you'll be proficient in utilizing the capabilities of the Python ecosystem to implement various image processing techniques effectively.
Table of Contents (11 chapters)

Implementing histogram matching

Histogram matching is an image processing task where an image is altered in such a way that its histogram matches the histogram of another reference (template) image's histogram. The algorithm is described as follows:

  1. Compute the cumulative histogram for each image.
  2. For any given pixel value, xi, in the input image, find the corresponding pixel value, xj, in the output image by matching the input image's histogram with the template image's histogram (G(xi)=H(xj), as shown in the following diagram.
  3. Replace pixel xi in the input with xj as shown in the following diagram:

In this recipe, we will implement histogram matching for colored images on our own.

Getting ready

As usual...