Image processing and computer vision technologies, combined with the rapid advancements in generative AI, have become foundational to many modern applications. As visual data continues to grow exponentially, the ability to analyze, interpret, and generate images using advanced algorithms and AI is more critical than ever for driving innovation across industries.
This book provides a thorough exploration of advanced techniques and practical implementations in the field of computer vision. This book offers a problem-oriented approach that bridges traditional image processing with modern machine learning and generative AI methods. This new edition significantly expands into specialized domains with medical imaging applications using professional libraries like pydicom, ITK, and nnUNet for clinical diagnosis, including COVID-19 detection and brain tumor segmentation, plus remote sensing analysis with satellite processing.
By the end of this book, readers will have developed strong practical skills in both classical and cutting-edge image processing and computer vision techniques, empowered to confidently design, implement, and adapt solutions across a wide range of real-world applications. They will emerge with a deep understanding of theory, hands-on coding experience, and the ability to leverage AI and generative models to push the boundaries of visual computing.
What you will learn
● Restore and enhance images using classical and deep learning methods.
● Segment images with advanced clustering and neural network techniques.
● Extract and match features for image alignment and recognition.
● Build and train image classifiers with ML and AI.
● Learn advanced restoration and inpainting techniques using cutting-edge deep learning models.
● Explore specialized domain expertise in medical imaging applications using professional libraries.
Who this book is for
This book is ideal for undergraduate and graduate students, researchers, and professionals in computer vision, image processing, and AI. It also serves computer vision engineers, image analysts, data scientists, software engineers, and industry practitioners seeking practical, hands-on expertise using Python.
Table of Contents
1. Image Restoration and Inverse Problems in Image Processing
2. More Image Restoration and Image Inpainting
3. Image Segmentation
4. More Image Segmentation
5. Image Feature Extraction and Its Applications: Image Registration
6. Applications of Image Feature Extraction
7. Image Classification
8. Object Detection and Recognition
9. Application of Image Processing and Computer Vision in Medical Imaging
10. Application of Image Processing and Computer Vision in Medical Imaging and Remote Sensing
11. Miscellaneous Problems in Image Processing and Computer Vision
Sandipan Dey is an author and data science enthusiast with a wide range of interests, including machine learning, deep learning, image processing, and computer vision. He has worked across various domains in data science, such as recommender systems, predictive modeling for the events industry, sensor localization, sentiment analysis, and device prognostics.
