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图像融合:理论与应用

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图像融合:理论与应用

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《图像融合:理论与应用》评述了图像融合研究领域的最新动态,以图像融合体系——像素级、特征级、决策级融合为主线,系统介绍图像融合的基本概念、基本理论、最新研究成果及应用实例。全书共10章,上篇为理论研究篇,主要内容有:图像融合概念、基本原理和结构;图像融合预处理;多源图像像素级、特征级、决策级融合方法;多源图像优化融合;多源动态图像融合;多源图像融合评价方法。下篇为应用实践篇,主要内容有:多源图像融合实例Ⅰ——合成孔径雷达与前视红外图像融合系统;多源图像融合实例Ⅱ——空间信息处理开发平台。《图像融合:理论与应用》是作者在近些年致力于图像融合研究工作的基础上撰写而成的,集中反映了作者及其研究团队的最新研究成果,也在一定程度上反映了国内外在图像融合领域的最新研究进展。
《图像融合:理论与应用》可作为高等学校高年级本科生、研究生学习图像融合的教材和教学参考书,也可作为从事图像融合研究和应用的科技人员的参考书。
Author Description

敬忠良 国家教育部第二批“长江学者奖励计划”特聘教授,博士生导师。1997-1998和1999年分别在美国加州大学伯克利分校和南伊利诺大学作高级访问学者和访问教授,现任上海交通大学空天科学技术研究院常务副院长。长期从事智能信息处理与控制理论及应用研究,先后主持和承担多项国家重点和重大项目;出版专著2部,发表论文150多篇,获授权国家发明专利20余项,软件著作权2项。论著被SCI、El等国际权威索引刊物收录100余次。先后荣获国家科技进步奖1项,全国优秀科技图书二等奖1项,部委级科技进步一等奖2项、二等奖6项,国家和省部级荣誉奖9项1其中1994年获第四届“中国青年科技奖”,1995年获国务院政府特殊津贴,1999年“中国航空工业突出贡献中青年专家”称号,2000年入选国家“百千万人才工程”第一、二层次。
Catalogue

上篇 理论研究篇
第1章 绪论
引言
1.1 图像融合的基本概念
1.2 图像融合的基本原理和结构
1.3 图像融合的发展现状和研究热点
1.4 本书内容概要
参考文献

第2章 图像融合预处理
引言
2.1 图像增强
2.1.1 空间域增强
2.1.2 频率域增强
2.1.3 彩色增强
2.1.4 图像运算
2.1.5 多光谱增强
2.2 图像校正
2.3 图像配准
2.3.1 基于灰度信息的图像配准方法
2.3.2 基于变换域的图像配准方法
2.3.3 基于特征的图像配准方法
2.4 图像的插值与重采样算法
2.4.1 主要插值算法
2.4.2 加权拉格朗日插值算法及其对比
本章小结
参考文献

第3章 多源图像像素级融合
引言
3.1 多源图像像素级融合常用算法
3.2 多源图像融合中的多尺度分解方法
3.2.1 拉普拉斯金字塔变换
3.2.2 对比度金字塔变换
3.2.3 梯度金字塔变换
3.2.4 离散小波变换
3.2.5 离散小波框架变换
3.2.6 改进的多尺度分解方法
3.2.7 实验结果及评价
3.3 基于多尺度分解的传统多源图像像素级融合算法
3.4 基于多尺度分解的改进多源图像像素级融合算法
3.4.1 多传感器图像融合算法
3.4.2 多聚焦图像融合算法
3.4.3 遥感图像融合算法
本章小结
参考文献

第4章 多源图像特征纫融合
引言
4.1 基于梯度特征的多尺度图像融合方法
4.1.1 基于梯度特征的多尺度变换方法
4.1.2 基于梯度特征的多尺度变换方法融合策略
4.2 联合纹理和梯度特征的多尺度图像融合方法
4.2.1 联合纹理和梯度特征的多尺度变换方法
4.2.2 基于梯度特征的多尺度图像融合方法
4.3 基于模糊区域特征的多尺度图像融合方法
4.3.1 基于区域的图像融合算法
4.3.2 基于模糊区域特征的图像融合方法
4.3.3 基于模糊区域特征的图像融合方法
本章小结
参考文献

第5章 多源图像决策级融合
引言
5.1 基于表决法的决策级融合算法
5.2 基于D-S证据理论的决策级融合算法
5.3 基于贝叶斯推理的决策级融合算法
5.4 基于求和规则的决策级融合算法
5.5 基于极大、极小值规则的决策级融合算法
5.5.1 最大值规则
5.5.2 最小值规则
5.6 基于模糊积分的决策级融合算法
5.7 决策级图像融合算法实现结果
本章小结
参考文献

第6章 多源图像优化融合
引言
6.1 基于IHS变换的图像融合彩色畸变分析
6.2 改进的IHs融合方法研究
6.3 基于像素和特征的联合最优融合研究
6.3.1 多分辨率图像的分解与重构
6.3.2 多分辨率图像小波分解后的统计特性
6.3.3 基于小波统计特性的联台最优融合方法(UOF)
6.4 基于模糊积分的最优融合研究
6.4.1 UOF算法的简化
6.4.2 模糊积分及其综合单因素指标的应用
6.4.3 基于模糊积分的最优融合(FOF)
本章小结
参考文献

第7章 多源动态图像融合
引言
7.1 多传感器动态图像融合体系
7.2 多传感器动态图像融合算法
7.2.1 序列图像超分辨率复原
7.2.2 运动目标检测
7.2.3 基于超分辨率复原和运动目标检测的动态图像融合规则
7.3 实验结果及评价
本章小结
参考文献

第8章 多源图像融合评价方法
引言
8.1 多源图像融合评价方法研究的必要性
8.2 多源图像融合评价方法研究
8.2.1 图像融合的定性评价
8.2.2 图像融合的定量评价指标
8.3 高光谱数据信噪比估算研究
8.3.1 高光谱数据信噪比估算研究的必要性
8.3.2 信噪比估算方法
本章小结
参考文献

下篇 应用实践篇
第9章 多源图像融合实例I——合成孔径雷达与前视红外图像融合系统
引言
9.1 软件系统功能及整体设计
9.1.1 软件系统功能
9.1.2 软件整体设计
9.2 软件模块介绍
9.2.1 图像增强模块
9.2.2 图像配准模块
9.2.3 图像融合模块
9.3 机载多传感器图像融合实例
9.3.1 机载前视红外与可见光图像融合
9.3.2 机载前视红外与微光夜视图像融合
本章小结
参考文献

第10章 多源图像融合实例Ⅱ——空间信息处理开发平台
引言
10.1 构建数字城市空间信息处理开发平台的必要性
10.2 空间信息处理开发平台的体系结构设计和模块功能实现
10.2.1 空间信息处理开发平台的总体设计
10.2.2 空间信息处理开发平台各功能模块设计和实现
10.3 卫星多源遥感图像的典型应用
10.4 机载多源遥感图像的典型应用
本章小结
参考文献
Book Abstract

2.假彩色增强
假彩色增强是彩色增强中最常用的一种方法,它与伪彩色增强不同,如遥感图像的假彩色增强处理的对象是同一景物的多光谱图像。众所周知,计算机显示器的彩色显示系统是根据三原色加色法合成原理,即由三个电子枪分别在屏幕上形成红、绿、蓝三个原色像而合成彩色图像的,因此,对于多波段遥感图像,选择其中的某三个波段,分别赋予红、绿、蓝三种原色,即可在屏幕上合成彩色图像。由于三个波段原色的选择是根据增强目的决定的,与原来波段的真实颜色不同,因此合成的彩色图像并不表示地物真实的颜色,这种合成称为假彩色合成。
3.彩色变换
计算机彩色显示器的显示系统采用的是RGB色彩模型,即图像中的每个像素通过红、绿、蓝三种色光,由多光谱图像的三个波段合成的彩色图像实际上只显示在R、G、B空间中。除此之外,遥感图像处理系统中还经常会采用IHs模型。亮度(Intensity,I)、色度(Hue,H)、饱和度(saturation,S)称为色彩的三要素,IHS模型不是基于色光混合来再现颜色的,但它表示的彩色与人眼看到的颜色更为接近。RGB和IHs两种色彩模式可以相互转换,有些处理在某个彩色系统中可能更方便。把RGB系统变换为IHS系统称为IHs正变换;IHs系统变换为RGB系统称为IHS逆变换。
Introduction

图像融合是将两个或者两个以上的传感器在同一时间或不同时间获取的关于某个具体场景的图像或者图像序列信息加以综合,以生成一个新的有关此场景解释的信息处理过程,而这个解释是从单一传感器获取的信息中无法得到的。图像融合的目的是减少不确定性。
20世纪90年代以来,图像融合技术的研究呈不断上升趋势,应用的领域也遍及对地观测、机场导航、安全监控、智能交通、医学成像与诊断、人类视觉辅助、地理信息系统、智能交通、智能制造、工业过程以及军事领域,并日益为众多的研究者所关注。但是,图像融合方法仍有许多问题值得进一步研究。主要包括图像融合的理论体系、图像噪声对图像融合的影响、图像融合的客观评价方法等。此外,多源动态图像的融合处理以及图像优化融合已逐步成为新的研究热点和难点。
近些年来,国内外研究者在图像融合领域取得了丰硕的研究成果。然而,迄今为止尚没有一本系统介绍图像融合理论、方法和应用的书籍,使得很多初学者感到入门困难,这一现象不利于推动图像融合研究和应用的进一步深入和普及。有鉴于此,我们将近几年的最新研究成果总结于此,与读者共勉。
本书仅就多源图像融合中的若干理论方法问题进行探讨,许多工作还有待今后进一步研究和完善。
本书共分10章。第1章为绪论,第2章介绍图像融合预处理方法,第3章论述多源图像像素级融合,第4章研究多源图像特征级融合,第5章阐述多源图像决策级融合,第6章研究多源图像优化融合方法,第7章论述多源动态图像融合方法,第8章给出多源图像融合评价方法,第9章为多源图像融合实例I——合成孔径雷达与前视红外图像融合系统,第10章为多源图像融合实例Ⅱ——空间信息处理开发平台。全书由敬忠良、肖刚、李振华统稿。

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