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Hands-On Image Processing and Computer Vision with Python
Hands-On Image Processing and Computer Vision with Python

Hands-On Image Processing and Computer Vision with Python: From image processing fundamentals to modern computer vision and generative AI , Second Edition

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Profile Icon Sandipan Dey
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₹4096.99
Paperback Jun 2026 770 pages 2nd Edition
eBook
₹999.99 ₹3276.99
Paperback
₹4096.99
Paperback + Subscription
₹1000 Monthly
Arrow left icon
Profile Icon Sandipan Dey
Arrow right icon
₹4096.99
Paperback Jun 2026 770 pages 2nd Edition
eBook
₹999.99 ₹3276.99
Paperback
₹4096.99
Paperback + Subscription
₹1000 Monthly
eBook
₹999.99 ₹3276.99
Paperback
₹4096.99
Paperback + Subscription
₹1000 Monthly

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Hands-On Image Processing and Computer Vision with Python

Foundations of Digital Image Processing

Part 1 builds the essential mathematical, algorithmic, and computational foundations required for all subsequent topics in the book. It begins with the fundamentals of digital images, including representation, sampling, quantization, and image formation, and progresses toward practical image manipulation using Python. Readers are introduced to core programming workflows using NumPy, PIL, OpenCV, and scikit-image for reading, transforming, and visualizing images. The part then develops a strong theoretical and applied understanding of spatial and frequency-domain analysis. Topics include Fourier transforms, discrete convolution, correlation, filtering theory, and the relationship between spatial and spectral representations of images. Emphasis is placed on understanding how image structure can be analyzed and modified using mathematical operators.

Finally, classical image enhancement and filtering techniques are introduced, including smoothing, sharpening, and basic restoration concepts. By the end of this part, readers will have a solid foundation in both the mathematical principles and practical tools required to work effectively with digital images and prepare for more advanced computer vision and deep learning concepts.

This part contains the following chapters:

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Key benefits

  • Master end-to-end image processing and computer vision workflows using Python
  • Build visual AI systems with classical, deep learning, and generative AI techniques
  • Apply theory with production-ready implementations using leading Python libraries
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

Analyzing and understanding visual data has become essential in modern applications such as healthcare, security, remote sensing, manufacturing, and digital media. This book provides a hands-on guide to image processing and computer vision using Python, following a practical approach that bridges theory with implementation. As you progress through the chapters, you will develop proficiency in Python 3 and implement algorithms spanning classical image processing, modern computer vision, and state-of-the-art (SOTA) deep learning and generative AI. The book covers image enhancement, restoration, filtering, segmentation, feature extraction, classification, and object detection using libraries including NumPy, OpenCV, PIL, SciPy, scikit-image, scikit-learn, TensorFlow, Keras, and PyTorch. Advanced chapters introduce CNNs, Vision Transformers, transformer-based segmentation, modern detection frameworks, GANs, diffusion models, foundation models, image-to-image translation, super-resolution, and multimodal vision-language understanding. Real-world applications span medical imaging, remote sensing, banking, augmented reality, autonomous driving, industrial inspection, and intelligent visual analytics. By the end of the book, you will be equipped to design and implement real-world visual computing solutions. *Email sign-up and proof of purchase required

Who is this book for?

Python developers, engineers, applied researchers, students, and AI practitioners who want to build end-to-end image processing and computer vision systems. A working knowledge of Python is required, while familiarity with linear algebra, calculus, and basic machine learning concepts will help you get the most from the advanced topics.

What you will learn

  • Build image processing and computer vision pipelines
  • Apply image enhancement, restoration, and segmentation
  • Implement image classification and object detection models
  • Explore CNNs, Vision Transformers, and attention models
  • Generate and edit images using GANs and diffusion models
  • Develop multimodal vision-language AI applications
  • Apply visual AI across diverse real-world domains
  • Implement super-resolution, style transfer, and image-to-image translation

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jun 30, 2026
Length: 770 pages
Edition : 2nd
Language : English
ISBN-13 : 9781837636235
Category :
Concepts :

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Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon A monthly credit and 50% off any future digital purchases.

Product Details

Publication date : Jun 30, 2026
Length: 770 pages
Edition : 2nd
Language : English
ISBN-13 : 9781837636235
Category :
Concepts :

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Table of Contents

19 Chapters
Part 1: Foundations of Digital Image Processing Chevron down icon Chevron up icon
Getting Started with Digital Image Processing Chevron down icon Chevron up icon
Image Manipulation Chevron down icon Chevron up icon
More Image Manipulation Chevron down icon Chevron up icon
Sampling and Fourier Transform Chevron down icon Chevron up icon
Convolution and Spatial/Frequency Domain Filtering Chevron down icon Chevron up icon
Frequency Domain Filtering Chevron down icon Chevron up icon
Part 2: Image Enhancement and Restoration Techniques Chevron down icon Chevron up icon
Image Enhancement Chevron down icon Chevron up icon
Image Enhancements Using Derivatives Chevron down icon Chevron up icon
Image Restoration: Inverse Problems in Imaging Chevron down icon Chevron up icon
Part 3: Computer Vision and Generative AI Chevron down icon Chevron up icon
Image Segmentation: From Classical Methods to Deep Learning Chevron down icon Chevron up icon
More Deep Learning Methods for Image Segmentation Chevron down icon Chevron up icon
Image Classification and Object Detection Chevron down icon Chevron up icon
Generative AI in Image Processing and Computer Vision Chevron down icon Chevron up icon
Unlock Your Exclusive Benefits Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
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