【作者】 张易凡；

【导师】 何明一；

【作者基本信息】 西北工业大学 ， 信号与信息处理， 2004， 硕士

【摘要】 遥感影象的数据融合是当今遥感技术领域中的一个研究热点。随着遥感信息获取手段的增多以及遥感技术的发展，遥感影象的融合受到了越来越多的关注。本文结合课题，在对小波理论和遥感图象融合技术进行了较为系统地学习和总结的基础之上，重点研究了以小波分析和无监督分类为工具的遥感图象融合方法及其算法仿真。 本文首先从小波理论在信号与信息处理学科领域中的应用角度对小波理论进行了系统的总结和介绍，分别利用Mallat算法和Trous算法实现了图象的正交小波变换和冗余小波变换。然后总结了现有典型的基于正交小波变换的像素级融合算法和基于冗余小波变换的图象融合算法，使用了标准差、信息熵和平均梯度三个标准作为融合结果的客观评价参数，并从理论上分析了各种算法的优劣。在以上分析的基础之上，作者提出了一种基于源图象活跃度和相似度的像素级融合算法，经过实验比较证明该算法的融合结果质量较同类算法有大幅度的提高。通过对图象纹理及其在多光谱图象融合中作用的深入研究，作者又提出了一种基于冗余小波纹理特征的重要中心系数(SCC)融合算法，通过与其它同类融合算法结果的比较证明了该算法在提高融合结果质量上的先进性。最后，还介绍了基于主成分分析(PCA)的多光谱图象融合方法以及非监督分类的方法，并实现了基于非监督分类的多光谱图象融合算法。更多还原

【Abstract】 Data fusion of remote-sensing images is one of the most interesting problems in the field of remote sensing technology. With the increase of the means to acquire remote information and the development of remote-sensing technology, remote-sensing image fusion has attracted more and more attention in recent years. In this paper, theories about wavelet analysis and image fusion are reviewed and remote-sensing image fusion is realized using wavelet analysis and unsupervised classification.First, wavelet transform theories are systematically reviewed and summarized from the point of view of signal and information processing. 2-D orthogonal wavelet transform and redundant wavelet transform are realized by use of Mallat algorithm and Trous algorithm respectively. Then typical existent fusion algorithms based on orthogonal and redundant wavelet transform are summarized. Standard deviation, entropy and average grads are advised to be the objective evaluation parameters. And the characteristics of each algorithm are analyzed theoretically. According to this analysis, a new pixel-level fusion algorithm based on the activity and similarity of source images is proposed and its performance is tested to be superior to the congeneric algorithms. By in-depth research of image texture and its application in multispectral image fusion, Significant Central Coefficient (SCC) algorithm based on redundant wavelet texture is proposed and its performance is tested to be also superior to the congeneric algorithms in the way of enhancing fusion quality. In the end, multispectral image fusion algorithms based on Principal Component Analysis and clustering algorithms are introduced. Multispectral image fusion based on unsupervised classification is realized.更多还原