一种新的基于2DPCA的遥感图像融合方法  

A novel image fusion method based on 2DPCA

作　　者：吴学明[1] 杨武年[1] 张章华[2] 

机构地区：[1]成都理工大学遥感与GIS研究所,四川成都610059 [2]成都理工大学信息工程学院,四川成都610059

出　　处：《微计算机信息》2009年第9期309-311,262,共4页Control & Automation

摘　　要：作为一种图像融合的重要技术,PCA已在遥感领域得到了较为广泛的应用。但这种方法也有缺点:首先,在对图像进行PCA分析时需将图像转换为一维向量来实现,从而不能有效利用图像的结构信息;其次,融合后的图像空间分辨率改善明显,但光谱信息损失严重。为解决些问题,我们提出了一种基于2DPCA的遥感图像融合方法。与PCA融合方法相比,该方法的主要特点为:首先,2DPCA是直接对图像矩阵进行,而不是对一维向量,这样就可以有效利用图像的结构信息;其次,融合后的图像不仅空间分辨率大大提高,而且保持了良好的光谱信息。本文的研究和实验证明这种新的图像融合方法是有效的。Principal Component Analysis （PCA）, as a key .technique of image fusion, has been widely applied in remote sensing. However, PCA has two weaknesses. One is that an image must be transformed into a 1-D vector when PCA is applied to the image. The other is that the spectral information is badly lost in the fused image, although the spatial resolution is apparently improved. To avoid these disadvantages of PCA, this paper shows a novel image fusion method based on two-dimensional PCA （2DPCA）, which is directly applied to the image matrices instead of 1D vector. Accordingly, the structural information of the image is effectively utilized. Furthermore, with this new technique, not Only the spatial resolution of the fused image is greatly improved, but also the spectral information of that is well preserved. The results of our experiment prove the validity of this method proposed.

关 键 词：图像融合 遥感 PCA 2DPCA 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]