Digital Image Processing Using Python (Paperback)

Manish Kashyap

ISBN 10: 9365898919 / ISBN 13: 9789365898910

Published by BPB Publications, New Delhi, 2024

About this Item

Paperback. This book offers a comprehensive exploration of digital image processing, combining theoretical foundations with practical applications. Starting with fundamental concepts like image representation and pixel neighborhoods, the book teaches Python programming and essential libraries for image manipulation. It covers a wide range of techniques, including spatial and frequency domain filtering, non-linear processing, noise reduction, wavelet transforms, and binary morphology. Advanced topics such as phase-based processing, multi-resolution analysis, and morphological operations are also explored in depth. The book provides practical examples and exercises to reinforce learning and equip readers with the skills needed to effectively process and analyze digital images for various applications. Builds a strong foundation in digital image processing, covering essential topics from basics to advanced techniques. Includes practical exercises to master Python programming and essential libraries like OpenCV and NumPy for image manipulation tasks. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9789365898910

Bibliographic Details

• Title: Digital Image Processing Using Python (Paperback)
• Publisher: BPB Publications, New Delhi
• Publication Date: 2024
• Language: English
• ISBN 10: 9365898919
• ISBN 13: 9789365898910
• Binding: Paperback
• Condition: new

About this title

Synopsis

Description

“Digital Image Processing Using Python" offers a comprehensive guide to mastering image processing techniques through practical Python implementations. It equips you with the essential tools and knowledge to manipulate, analyze, and transform digital images using the powerful programming language, Python.

This book offers a comprehensive exploration of digital image processing, combining theoretical foundations with practical applications. Starting with fundamental concepts like image representation and pixel neighborhoods, the book teaches Python programming and essential libraries for image manipulation. It covers a wide range of techniques, including spatial and frequency domain filtering, non-linear processing, noise reduction, wavelet transforms, and binary morphology. Advanced topics such as phase-based processing, multi-resolution analysis, and morphological operations are also explored in depth. The book provides practical examples and exercises to reinforce learning and equip readers with the skills needed to effectively process and analyze digital images for various applications.

By integrating Python code with visual examples, you will gain practical experience and insights that are directly applicable to your work. This approach ensures that you not only learn theoretical concepts but also understand how to implement them effectively in real-world situations.

Key Features

● Builds a strong foundation in digital image processing, covering essential topics from basics to advanced techniques.

● Includes practical exercises to master Python programming and essential libraries like OpenCV and NumPy for image manipulation tasks.

● Applies concepts to real-world scenarios like image restoration, object detection, and medical imaging.

What you will learn

● Implement image processing techniques using Python libraries and tools.

● Understand core concepts like filtering, segmentation, and enhancement.

● Apply practical Python code to real-world image processing tasks.

● Develop skills to analyze and manipulate digital images effectively.

● Create and visualize image processing algorithms with hands-on examples.

Who this book is for

This book is perfect for undergraduate and master's level students seeking to grasp image processing concepts or professionals working in fields like computer vision, artificial intelligence, or medical imaging.

Table of Contents

1. Introduction to Digital Images

2. Python Fundamentals and Related Libraries

3. Playing with Digital Images

4. Spatial Domain Processing

5. Frequency Domain Image Processing

6. Non-linear Image Processing and the Issue of Phase

7. Noise and Image Restoration

8. Wavelet Transform and Multi-resolution Analysis

9. Binary Morphology