SPOT5全色波段与ASTER多光谱影像融合方法的比较研究
Comparison Between SPOT5 Pan and ASTER Multispectral Image Fusion Method

多源遥感影像数据融合可以将不同来源数据包含的优势信息重构为新的信息载体，进而为解 决实际问题提供更丰富的信息。与TM，CBERS-1等影像数据相比，ASTER多光谱影像在短波红外波段具有更强的优势，因此将其与SPOT5全色波段进行融合可为解决实际问题提供更多的细微信息。本文选取主成分分析变换（Principal component analysis，PC A）、比值变换（Brovey）、格兰姆-施密特变换（Gram-Schmidt，GS）和小波变换4种融合方法进行对比研究，实验结果表明PCA变换和GS变换适用于这两种影像融合。
Remote sensing image fusion is one of the effective ways to solve multi-source remote sensing data integrated performance. ASTER multi-spectral image is better at spectral information than TM and CBERS-1, except for the lack of spatial resolution. The fusion of SPOT pan and ASTER multispectral is significant. Here, we choose the PCA transform, Brovey transform, Gram-Schmidt (GS) transform and wavelet transform fusion method to compare. The results show that the PCA transform and GS transform are suitable for the fusion of SPOT5 pan and ASTER multi-spectral image.