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Jingdong book

数字图像处理：原理与实践（MATLAB版）

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Jingdong book

数字图像处理：原理与实践（MATLAB版）

Name: 数字图像处理：原理与实践（MATLAB版）
Brand: Jingdong book
SKU: 3118210601
Price: 33.63 USD
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《数字图像处理：原理与实践（MATLAB版）》全面系统地介绍了数字图像处理技术的理论与方法，内容涉及几何变换、灰度变换、图像增强、图像分割、图像去噪、小波变换、形态学处理、多尺度融合、偏微分方程应用、正交变换与图像压缩、边缘及轮廓检测、图像复原、图像去雾、多尺度空间构建与特征匹配等15大核心话题。工欲善其事，必先利其器。《数字图像处理：原理与实践（MATLAB版）》所有算法均配有完整的MATLAB实现代码，并以此为基础详细介绍了MATLAB中与图像处理有关的近200个函数的使用方法，便于读者学习与实践。此外，《数字图像处理：原理与实践（MATLAB版）》还提供了丰富的在线支持资源，方便为读者答疑解惑及提供辅助资料下载。

Author Description

左飞，服务于中国规模最大的移动通信运营商，业余时间他撰写了多部计算机方面的著作，并译有《编码》、《提高C++性能的编程技术》等经典名著。

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第1章绪论
1.1 数字图像处理概述
1.1.1 图像与数字图像
1.1.2 数字图像处理研究的内容
1.1.3 数字图像处理的应用
1.2 MATLAB概述
1.2.1 MATLAB的发展
1.2.2 MATLAB的特点
1.2.3 MATLAB的结构
1.3 在MATLAB中处理数字图像
1.3.1 MATLAB中的图像存储
1.3.2 MATLAB中的图像转换
1.3.3 MATLAB中图像的基本操作
本章参考文献及推荐阅读材料

第2章图像的点运算
2.1 灰度直方图
2.1.1 灰度直方图简介
2.1.2 基本原理
2.1.3 编码实现
2.2 灰度线性变换
2.2.1 基本原理
2.2.2 编码实现
2.3 灰度非线性变换
2.3.1 灰度对数变换
2.3.2 灰度幂次变换
2.3.3 灰度指数变换
2.4 灰度拉伸
2.4.1 基本原理
2.4.2 编码实现
2.5 灰度均衡
2.5.1 基本原理
2.5.2 编码实现
2.6 直方图规定化
2.6.1 基本原理
2.6.2 编码实现
本章参考文献及推荐阅读材料

第3章图像的几何变换
3.1 图像几何变换的基本理论
3.1.1 图像几何变换概述
3.1.2 图像几何变换的数学描述
3.2 图像的平移变换
3.2.1 效果预览
3.2.2 基本原理
3.2.3 编程实现
3.3 图像的镜像变换
3.3.1 效果预览
3.3.2 基本原理
3.3.3 编程实现
3.4 图像的转置
3.4.1 效果预览
3.4.2 基本原理
3.4.3 编程实现
3.5 图像的缩放
3.5.1 效果预览
3.5.2 基本原理
3.5.3 插值算法介绍
3.5.4 编程实现
3.6 图像的旋转
3.6.1 效果预览
3.6.2 基本原理
3.6.3 编程实现
本章参考文献及推荐阅读材料

第4章图像的增强处理
4.1 卷积积分与邻域处理
4.1.1 理解卷积积分的概念
4.1.2 卷积应用于图像处理的原理
4.1.3 邻域处理的基本概念
4.1.4 运用模板实现邻域处理
4.2 图像的简单平滑
4.2.1 图像的简单平滑原理
4.2.2 简单平滑的编码实现
4.3 图像的高斯平滑
4.3.1 平滑线性滤波器
4.3.2 高斯平滑的原理
4.3.3 高斯分布
4.3.4 高斯平滑的算法实现
4.4 图像的中值滤波
4.4.1 统计排序滤波器
4.4.2 图像中值滤波的原理
4.4.3 图像中值滤波的算法实现
4.5 图像的双边滤波
4.6 图像的拉普拉斯锐化
4.6.1 图像的锐化
4.6.2 拉普拉斯锐化的原理
4.6.3 拉普拉斯锐化的编码实现
本章参考文献及推荐阅读材料

第5章图像的形态学处理
5.1 数学形态学
5.2 一些必要的概念和符号约定
5.3 图像的腐蚀
5.3.1 腐蚀原理
5.3.2 编程实现
5.4 图像的膨胀
5.4.1 膨胀原理
5.4.2 编程实现
5.5 腐蚀和膨胀的性质及应用
5.5.1 腐蚀和膨胀的代数性质
5.5.2 腐蚀和膨胀的应用
5.6 开运算和闭运算
5.6.1 开运算
5.6.2 闭运算
5.6.3 编程实现
5.6.4 开运算和闭运算的代数性质
5.7 图像形态学的其他运算
5.7.1 击中/不击中运算
5.7.2 细化处理
本章参考文献及推荐阅读材料

第6章边缘检测
6.1 基本概念及思想
6.1.1 边缘检测的基本概念
6.1.2 边缘检测的基本思想
6.2 基于梯度的常规方法
6.2.1 梯度算子及其离散化表示
6.2.2 用梯度算子进行边缘检测
6.2.3 带有方向信息的边缘检测
6.3 拉普拉斯算子
6.4 基于LoG和DoG的边缘检测
6.4.1 高斯拉普拉斯算子（LoG）
6.4.2 高斯差分算子（DoG）
6.5 Canny边缘检测算法
6.5.1 Canny准则
6.5.2 Canny算法与实现
本章参考文献及推荐阅读材料

第7章图像分割
7.1 豪格变换
7.1.1 平面坐标系的转换
7.1.2 Hough变换的思想
7.1.3 直线的Hough变换
7.1.4 圆的Hough变换
7.2 轮廓跟踪
7.2.1 区域表示方法
7.2.2 单区域跟踪
7.2.3 多区域跟踪
7.2.4 编码实现
7.3 种子填充
7.3.1 算法介绍
7.3.2 编码实现
7.4 区域分割
7.4.1 区域分裂与合并
7.4.2 编程实现
7.5 水域分割
7.5.1 从必备的基本概念开始
7.5.2 分水岭分割算法的原理
7.5.3 标记控制的分水岭算法
本章参考文献及推荐阅读材料

第8章正交变换与图像压缩
8.1 傅里叶变换
8.1.1 傅里叶变换的数学基础
8.1.2 傅里叶变换与傅里叶级数的关系
8.1.3 数字图像的傅里叶变换
8.1.4 快速傅里叶变换的算法
8.1.5 编程实现图像的快速傅里叶变换
8.2 离散余弦变换
8.2.1 基本概念及数学描述
8.2.2 离散余弦变换的快速算法
8.2.3 离散余弦变换的意义与应用
8.3 沃尔什-哈达玛变换
8.3.1 沃尔什函数
8.3.2 离散沃尔什变换及其快速算法
8.3.3 沃尔什变换的应用
8.4 卡洛南-洛伊变换
8.4.1 一些必备的基础概念
8.4.2 主成分变换的推导
8.4.3 编码实现主成分变换
8.4.4 应用K-L变换实现图像压缩
本章参考文献及推荐阅读材料

第9章小波变换及其应用
9.1 子带编码
9.1.1 数字信号处理基础
9.1.2 多抽样率信号处理
9.1.3 图像的子带分解
9.2 哈尔函数与哈尔变换
9.2.1 哈尔函数的定义
9.2.2 哈尔函数的性质
9.2.3 酉矩阵与酉变换
9.2.4 二维离散线性变换
9.2.5 哈尔基函数
9.2.6 哈尔变换
9.3 小波的数学基础
9.3.1 小波的历史
9.3.2 理解小波的概念
9.3.3 多分辨率分析
9.3.4 小波函数的构建
9.3.5 小波序列展开
9.3.6 离散小波变换
9.3.7 连续小波变换
9.3.8 小波的容许条件与基本特征
9.4 快速小波变换
9.4.1 快速小波正变换
9.4.2 快速小波逆变换
9.4.3 图像的小波变换
9.5 小波在图像处理中的应用
本章参考文献及推荐阅读材料

第10章偏微分方程与图像降噪
10.1 PM方程及其应用
10.1.1 一维热传导方程
10.1.2 各向异性扩散方程
10.1.3 PM扩散方程的实现
10.1.4 加性算子分裂
10.2 TV方法及其应用
10.2.1 泛函与变分法
10.2.2 全变分模型
10.2.3 TV算法的数值实现
10.2.4 基于TV的图像降噪实例
本章参考文献及推荐阅读材料

第11章图像复原
11.1 从图像的退化到复原
11.1.1 图像的退化模型
11.1.2 连续的退化模型
11.1.3 离散的退化模型
11.2 常规的图像复原示例
11.2.1 循环矩阵的对角化
11.2.2 逆滤波的基本原理
11.2.3 维纳滤波及其应用
11.2.4 露茜-理查德森算法
11.3 暗通道优先的图像去雾算法
11.3.1 暗通道的概念与意义
11.3.2 暗通道去雾霾的原理
11.3.3 算法实现与应用
11.3.4 算法不足及改进方向
本章参考文献及推荐阅读材料

第12章图像的特征检测
12.1 SIFT特征检测
12.1.1 尺度空间构造
12.1.2 空间极值检测
12.1.3 方向赋值
12.1.4 特征描述
12.1.5 算法实现
12.2 SURF特征检测
12.2.1 积分图
12.2.2 DoH近似
12.2.3 尺度空间表达
12.2.4 特征描述
12.2.5 算法实现
12.3 KAZE特征检测
12.3.1 非线性扩散滤波
12.3.2 尺度空间的构造
12.3.3 特征检测与描述
本章参考文献及推荐阅读材料

附录A 必不可少的数学基础
附录B 图像编码的理论基础

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