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)

Restoring an image with the constrained least squares filter

In this recipe, we shall demonstrate yet another filter named the Constrained Least Squares (CLS) filter in the frequency-domain. As the name of the filter suggests, it's an inverse (least squares) filter with an additional smoothness constraint that does not allow arbitrary high-frequency fluctuation in the restored image by imposing a smoothness constraint. You shall now learn how to implement a CLS filter and how to restore a degraded image by applying the filter on the image. Also, you shall compare the qualities of the restored images using different frequency-domain filter implementations such as inverse, Wiener, and CLS.

Getting ready

Let's first...