Digital Image Processing
Digital Image Processing
复制标题
DOI：
10.1007/978-1-4471-6684-9
复制
发表时间：
2016-03
期刊：
影响因子：
--
通讯作者：
W. Burger;M. Burge
中科院分区：
文献类型：
--
作者：
W. Burger;M. Burge
这本现代化的，独立的教科书从实践程序员的角度提供了对该领域的可访问的介绍，支持基本概念和技术的详细介绍，并提供了实际练习和充分制定的实施示例。这本备受期待的关于数字图像处理的权威教科书的第三版已经完全修订和扩展了新的内容，改进了插图和教材。主题和功能：包含关于几何图元拟合、随机特征检测（RANSAC）和最大稳定极值区域（MSER）的新章节。包括大多数章节的练习，并在相关网站上提供额外的补充材料和软件实现。所有示例都使用ImageJ，这是一个广泛使用的开源成像环境，可以在所有主要平台上运行。以数学形式逐步描述每个解决方案，作为抽象的伪代码算法，并作为可以轻松移植到其他编程语言的完整Java程序。在前言中提出了一个或两个学期课程的建议大纲。高级本科生和研究生会发现这本全面和丰富的例子教科书将作为理想的介绍数字图像处理。它也将证明是非常宝贵的研究人员和专业人士寻求一个实际集中的自学入门。
This modern, self-contained textbook provides an accessible introduction to the field from the perspective of a practicing programmer, supporting a detailed presentation of the fundamental concepts and techniques with practical exercises and fully worked out implementation examples. This much-anticipated 3rd edition of the definitive textbook on Digital Image Processing has been completely revised and expanded with new content, improved illustrations and teaching material. Topics and features: Contains new chapters on fitting of geometric primitives, randomized feature detection (RANSAC), and maximally stable extremal regions (MSER). Includes exercises for most chapters and provides additional supplementary materials and software implementations at an associated website. Uses ImageJ for all examples, a widely used open source imaging environment that can run on all major platforms. Describes each solution in a stepwise manner in mathematical form, as abstract pseudocode algorithms, and as complete Java programs that can be easily ported to other programming languages. Presents suggested outlines for a one-or two-semester course in the preface. Advanced undergraduate and graduate students will find this comprehensive and example-rich textbook will serve as the ideal introduction to digital image processing. It will also prove invaluable to researchers and professionals seeking a practically focused self-study primer.