Comparative Analysis of the Fusion Methods Based on GF-3 Radar and GF-1 Multispectral Data

摘要

To make better use of the advantages of radar and promote the application of image fusion based on radar data, the author uses different fusion methods based on GF-3 SAR and GF-1 MSS, and evaluates the fusion results by analyzing mean, variance, information entropy, average gradient, spectral distortion and correlation coefficient. The results show that HSV and GS transforms have the best performances in overall. PC is recognized as the third, while it is still remarkable that it has the best ability of spectral retention. And the specialty in NIR band makes PC more conducive for extraction of vegetation. Brovey and Multiplicative transforms are not effective in comparison.