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)

Improving image contrast with histogram equalization

In Chapter 1, Image Manipulation and Transformation, we saw how the contrast stretching operation can be used to increase the contrast of an image. However, it is just a linear scaling function that is applied to image pixel values, and hence the image enhancement is less drastic than its more sophisticated counterpart, histogram equalization. This recipe will show how to implement contrast stretching using the histogram equalization. It is also a point transform that uses a non-linear mapping that reassigns the pixel intensity values in the input image in such a way that the output image has a uniform distribution of intensities (a flat histogram), and thereby enhances the contrast of the image.

Getting ready

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