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Jingdong book

数字图像处理

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Jingdong book

数字图像处理

Name: 数字图像处理
Brand: Jingdong book
SKU: 3118188691
Price: 41.70 USD
Availability: OutOfStock

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Content Description

《数字图像处理》主要介绍了数字图像处理的基本概念、常用方法、实用技术和典型应用。全书分三大部分共13章，第一部分是数字图像处理基础，包括绪论、数字图像处理基础，分别介绍了数字图像处理的研究对象和研究内容、系统组成、人类视觉与色度学、图像数字化知识、数字图像的种类、图像文件格式与图像变换等相关知识；第二部分介绍图像处理的基本方法和技术，包括图像增强、图像恢复和图像压缩编码。第三部分讲述数字图像分析的基本原理和方法，包括图像分割、图像描述和图像分类识别，新理论在图像处理方面的应用。内容系统，重点突出，理论与实例并重。每章配有小结和习题。

Catalogue

前言
第1章绪论
1．1 图像与数字图像的表示
1．2 数字图像处理
1．3 数字图像处理方法
1．4 数字图像处理的主要研究内容
1．5 数字图像处理的应用实例
1．6 小结
习题
第2章数字图像处理的基本原理
2．1 图像的数字化
2．2 数字图像的储存格式
2．3 图像的直方图
2．4 像素间的基本关系
2．5 小结
习题
第3章图像变换
3．1 图像的正交变换
3．2傅里叶变换
3．3 离散余弦变换
3．4 小波变换
3．5 沃尔什变换
3．6 哈达玛变换
3．7 小结
习题
第4章图像增强
4．1 空间域图像增强
4．2 频域图像增强
4．3 彩色图像增强
4．4 小结
习题
第5章图像复原与重建
5．1 概述
5．2 图像的退化模型及估计
5．3代数恢复方法
5．4 频率域复原方法
5．5 几何校正
5．6 小结
习题
第6章图像压缩
6．1 概述
6．2 无损压缩
6．3 有损压缩
6．4 JPEG编码压缩
6．5 小结
习题
第7章图像分割
7．1 边缘检测
7．2 阈值与图像分割
7．3 基于区域的分割
7．4 基于形态学分水岭的分割
7．5 分形方法在图像分割中的应用
7．6 K均值方法在图像分割中的应用
7．7 小结
第8章图像匹配与识别
8．1 图像匹配
8。2 图像识别
8．3 关于模式识别的一些基本问题
8．4 小结
习题
第9章图像融合
9．1 简介
9．2 多传感器图像融合技术
9．3 像素级多传感器图像融合
9．4 像素级多传感器图像融合方法综述
9．5 多聚焦图像融合
9．6 多聚焦图像的评价方法
9．7 多聚焦图像融合方法分类与比较
9．8 基于小波变换的多聚焦图像融合
9．9 小结
习题
第10章遥感图像处理
10．1 遥感基础
l0．2 遥感图像目视判读
l0．3 遥感图像校正
10．4 遥感图像分类
l0．5 小结
第11章分形及其在数字图像处理中的应用
11．1 分形的发展
11．2 分形的定义
11．3分形维数
11．4 规则分形及其分形维数
11．5 不规则分形维数的测定
11．6 多重分形
11．7 归一化概率测度的测定方法
11．8 分形与数字图像处理
11．9 小结
第12章 Contourlet变换及其在图像处理中的应用
12．1 Contourlet变换基本理论
12．2 ContOurlet变换在图像处理中的应用
12．3 小结
习题
第13章图像超分辨率重建技术
13．1 图像超分辨率的相关概念
13．2 国内外超分辨重建技术研究概况
13．3 图像退化过程分析及成像系统模型
13．4 图像超分辨的数学物理基础及质量评价
13．5 频域解混叠图像超分辨重建法
13．6 空域POCS超分辨图像重建法
13．7 超分辨率重建技术应用领域及研究展望
13．8 小结
参考文献

Book Abstract

1．3 数字图像处理方法
数字图像处理的方法种类繁多，根据不同的分类标准可以得到不同的分类结果。根据数字图像处理方法处理的作用域不同，主要可以将数字图像处理方法分为空域图像处理方法和变换域图像处理方法。图像各像素点进行灰度上的变换处理，也可以对图像进行小区域模板的空域滤波等处理，以充分考虑像素邻域像素点对其的影响。
空域图像处理方法主要分为两大类，即邻域处理法和点处理法。
1．3．2 变换域图像处理方法
变换域图像处理方法是通过各种图像变换方法将图像从空域变换到相应的变换域，得到变换域系数阵列，然后在变换域中对图像进行处理，处理完成后再将图像从变换域进行反变换到空间域，得到最后的处理结果。
变换域图像处理方法所使用的图像变换主要有傅里叶变换、离散余弦变换、沃尔什变换、哈达玛变换、小波变换和轮廓波变换等。
1．4 数字图像处理的主要研究内容
1．4．1 数字图像处理的内容
图像处理的内容相当丰富，包括狭义的图像处理、图像分析与图像理解。
狭义的图像处理着重强调在图像之间进行的变换，是一个从图像到图像的过程，是比较低层的操作。狭义的图像处理主要是对图像进行各种加工，以改善图像的视觉效果，或对图像进行压缩编码以减少所需存储空间或传输时间，达到传输通路的要求。其特点是主要在像素级进行处理，处理的数据量非常大。
图像分析一般利用数学模型并结合图像处理的技术分析底层特征和上层结构，从而提取具有一定智能性的信息。图像分析主要是对图像中感兴趣的目标进行检测和测量，从而建立对图像目标的描述。图像分析是一个从图像到数值或符号的过程。
图像理解则是在图像分析的基础之上，基于人工智能和认知理论研究图像中各目标的性质和它们之间的相互联系，理解图像内容的含义及解译原来的客观场景，从而指导和规划行动。如果图像分析主要是以观察者为中心研究客观世界（主要研究可观察到的对象）的，那么图像理解在一定程度上是以客观世界为中心，借助知识、经验等把握整个客观世界的。
1．4．2 数字图像处理的主要研究方向
数字图像处理在科学技术和计算机技术的飞速发展的同时，将不断趋向成熟。目前，计算机设备价格的下降，通过万维网及互联网的网络通信带宽的扩展，图像数字化和图像显示设备的普及，低成本的数字图像处理系统的应用，为数字图像处理的持续发展创造了前所未有的机会，其数字图像处理的研究内容也将不断深入。下面对数字图像处理的主要研究方向进行详细介绍。
……

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