This book covers how to solve image processing problems using popular Python image processing libraries (such as PIL, scikit-image, python-opencv, scipy ndimage, and SimpleITK), machine learning libraries (scikit-learn), and deep learning libraries (TensorFlow, Keras). It will enable the reader to write code snippets to implement complex image processing algorithms, such as image enhancement, filtering, restoration, segmentation, classification, and object detection. The reader will also be able to use machine learning and deep learning models to solve complex image processing problems. 

The book will start with the basics and guide the reader to go to an advanced level by providing Python-reproducible implementations throughout the book. The book will start from the classical image processing techniques and explore the journey of evolution of the image processing algorithms all the way through to the recent advances in image processing/computer vision with deep learning. Readers will learn how to use the image processing libraries, such as PIL, scikit-image, and scipy ndimage in Python, which will enable them to write code snippets in Python 3 and quickly implement complex image processing algorithms, such as image enhancement, filtering, segmentation, object detection, and classification. The reader will learn how to use machine learning models using the scikit-learn library and later explore deep CNN such as VGG-19 with TensorFlow/Keras, use the end-to-end deep learning YOLO model for object detection, and DeepLab V3+ for semantic segmentation and neural-style transfer models. The reader will also learn a few advanced problems, such as image inpainting, gradient blending, variational denoising, seam carving, quilting, and morphing. By the end of this book, the reader will learn to implement various algorithms for efficient image processing.

This book follows a highly practical approach that will take its readers through a set of image processing concepts/algorithms and help them learn, in detail, how to use leading Python library functions to implement these algorithms.