Book Image

Hands-On Image Processing with Python

By : Sandipan Dey
Book Image

Hands-On Image Processing with Python

By: Sandipan Dey

Overview of this book

Image processing plays an important role in our daily lives with various applications such as in social media (face detection), medical imaging (X-ray, CT-scan), security (fingerprint recognition) to robotics & space. This book will touch the core of image processing, from concepts to code using Python. The book will start from the classical image processing techniques and explore the evolution of image processing algorithms up to the recent advances in image processing or computer vision with deep learning. We will learn how to use image processing libraries such as PIL, scikit-mage, and scipy ndimage in Python. This book will enable us to write code snippets in Python 3 and quickly implement complex image processing algorithms such as image enhancement, filtering, segmentation, object detection, and classification. We will be able to use machine learning models using the scikit-learn library and later explore deep CNN, such as VGG-19 with Keras, and we will also use an end-to-end deep learning model called YOLO for object detection. We will also cover a few advanced problems, such as image inpainting, gradient blending, variational denoising, seam carving, quilting, and morphing. By the end of this book, we will have learned to implement various algorithms for efficient image processing.
Table of Contents (20 chapters)
Title Page
Copyright and Credits
Dedication
About Packt
Contributors
Preface
Index

Seamless cloning and Poisson image editing


The goal of Poisson image editing is to perform seamless blending (cloning) of an object or a texture from a source image (captured by a mask image) to a target image. We want to create a photomontage by pasting an image region onto a new background using Poisson image editing. This idea is from the SIGGRAPH 2003 paper, Poisson Image Editing, by Perez et alia. The problem is first expressed in the continuous domain as a constrained variational optimization problem (the Euler-Lagrange equation is used to find a solution), and then can be solved using a discrete Poisson solver. The main task of the discrete Poisson solver is to solve a huge linear system. The central insight in the paper is that working with image gradients, instead of image intensities, can produce much more realistic results. After seamless cloning, the gradient of the output image in the masked region is the same as the gradient of the source region in the masked region. Additionally...