Digital Image Processing and Python Implementation
Tags
Summary
Editor's review
In terms of content, the book covers core topics including basic image operations, spatial-domain and frequency-domain filtering, image restoration, morphological processing, and image segmentation. The coverage is comprehensive and the difficulty gradient is well paced. A highlight is the moderate theoretical derivation provided for each key algorithm, supported by intuitive diagrams and runnable code snippets, which greatly lowers the learning barrier and makes abstract concepts operable and verifiable. For readers with basic Python and higher mathematics knowledge, the book offers an efficient, systematic path from beginner to intermediate level.
Amid the current boom in artificial intelligence and computer vision, the book upholds the foundational role of image processing and emphasizes building inner strength. It may not chase the latest deep learning models, but the underlying knowledge and programming paradigms it teaches are indispensable foundations for understanding and innovating with more advanced technologies. Overall, this is a rigorous, practical, and excellent work well suited for self-learners and university students in related majors as a core textbook or supplementary reading.
Who it's for
A good fit for
- University students or self-learners with basic Python programming skills who want to systematically study core digital image processing algorithms and their implementation
- Beginners in computer vision and artificial intelligence who want to solidify their knowledge of image processing fundamentals and programming skills
- Engineers who need to apply traditional image processing techniques in real projects and seek reliable principle references and code examples
- University teachers or training instructors looking for a textbook that combines theory and practice and is suitable for teaching an image processing course
Not a good fit for
- Readers who expect to quickly master deep learning for frontier applications such as image recognition and generation and are not interested in traditional image processing methods
- Complete beginners with no programming background and no knowledge of higher mathematics
Reading tips
- Read the chapters in order, implement the example code for each section hands-on, and try adjusting parameters to observe how the results change, thereby deepening understanding.
- When reading the theory, combine the diagrams and mathematical formulas in the book, and work through derivations or calculations on paper to grasp the core ideas of the algorithms.
- After finishing each chapter, try using the methods learned to solve a simple practical problem, or reproduce the basic image processing steps in a classic paper, to consolidate the knowledge system.
About the publisher
Posts & Telecom Press is known for its strengths in science and technology, computing, and information and communications titles, and has extended its publishing into photography, art, software learning, and inspirational growth, giving it a fairly diverse range. Its catalog includes computing and communications works such as Refactoring and Patterns (Revised Edition) and Huawei Switch Learning Guide (Second Edition), alongside bilingual collector's editions such as The Little Prince (Chinese-English-French illustrated collector's edition), The Great Gatsby, and Three Days to See. Beijing Ten Years: 1980-1990 and Ghost Blade: WLOP Personal Illustration Collection reflect its presence in photography and art. Its authors include Antoine de Saint-Exupéry, Helen Keller, Joshua Kerievsky, Wang Da, Zhang Zhaozeng, and WLOP.
Contents
- 版权信息
- 内容提要
- 编委会
- 序一
- 序二
- 前言
- chapter 01 数字图像处理基础知识
- 1.1 数字图像简介
- 1.2 图像采样和量化
- 1.3 图像的表示和可视化
- 1.4 像素间的关系
- 1.5 简单图像处理
- 1.6 小结
- 1.7 本章练习
- chapter 02 彩色图像处理初步
- 2.1 彩色图像的颜色空间
- 2.2 伪彩色图像处理
- 2.3 基于彩色的图像分割
- 2.4 彩色图像的灰度化
- 2.5 小结
- 2.6 本章练习
- chapter 03 空间滤波
- 3.1 空间滤波基础
- 3.2 平滑处理
- 3.3 锐化处理
- 3.4 混合空间增强
- 3.5 小结
- 3.6 本章练习
- chapter 04 频域滤波
- 4.1 傅里叶变换
- 4.2 傅里叶变换的性质
- 4.3 快速傅里叶变换
- 4.4 图像频域滤波
- 4.5 小结
- 4.6 本章练习
- chapter 05 图像特征提取
- 5.1 图像颜色特征提取
- 5.2 图像纹理特征提取
- 5.3 图像形状特征提取
- 5.4 图像边缘特征提取
- 5.5 图像点特征提取
- 5.6 小结
- 5.7 本章练习
- chapter 06 图像压缩
- 6.1 图像压缩简介
- 6.2 熵编码技术
- 6.3 预测编码
- 6.4 变换编码
- 6.5 JPEG编码
- 6.6 小结
- 6.7 本章练习
- chapter 07 图像小波变换与多分辨率
- 7.1 从傅里叶变换到小波变换
- 7.2 简单小波示例
- 7.3 图像多分辨率
- 7.4 图像小波变换
- 7.5 小结
- 7.6 本章练习
- 附录A Python开发环境配置及基本语法
- 参考文献
FAQ
What prior knowledge does this book require of readers?
Which versions of the Python libraries does this book use? How should the code environment be configured?
How is this book different from books that only teach OpenCV usage?
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About the author
Yue Yawei is an author about whom limited public information is available. The library holds one work by this author, Digital Image Processing and Python Implementation, which is classified under software learning. The title indicates that Yue Yawei's writing focuses on combining digital image processing with hands-on Python programming, aimed at readers who wish to study and implement image processing algorithms using the Python language. Books of this kind typically emphasize both theory and practice, explaining basic image operations, filtering, transforms, and feature extraction through concrete code examples, so that readers can understand and reproduce the algorithms in a software environment. Based on the available information, it is difficult to confirm Yue Yawei's personal background, professional identity, or other publications, and the author has only one work in the library, so any judgment of writing style and influence must rest on this single book. What can be stated is that the book offers readers an entry point to software learning and introductory image processing using Python as a practical tool, suitable as a supplementary text for related courses or self-study.
