In order to take full advantage of the multi-source remote sensing data, the concept of image fusion was proposed and nowadays, many fusion algorithms have been produced, so the adaptability of the algorithm has become a hot topic. This article aiming at the panchromatic and multispectral images of Worldview-2, uses the different fusion methods, including PCA, HPF, Gram-Schmidt and wavelet transform, to fuse the image, and evaluates the results from the aspects of the statistical information, spectral information and spatial characteristics. Then it takes the extracting vegetation as an example, analyzes the applicability of different fusion methods. The research shows that Gram-Schmidt and wavelet transform have better fusion quality and Gram-Schmidt is the most suitable method to extract vegetation for Worldview-2.

Date Published: 26 November 2014
PDF: 9 pages
Proc. SPIE 9263, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications V, 92631V (26 November 2014); doi: 10.1117/12.2068844

Published in SPIE Proceedings Vol. 9263:
Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications V
Allen M. Larar; Makoto Suzuki; Jianyu Wang, Editor(s)