Comparison of quality evaluation methods for image fusion of farmland remote sensing

In order to compare fusion effects, evaluate fusion algorithms and optimize fusion process, three quantitative evaluation indexes were presented on the basis of analyzing quality evaluation methods of remote sensing image fusion: imagery brightness index, spatial information index, and spectral information index. Finally, optical remote sensing imagery fusion was taken for example. The applicability and effectiveness of four pixels level fusion algorithms were verified by means of simulation experiment. IHS transformation distorted the spectral characteristics of imagery, so the feature spectra was easily to become vestigial; Wavelet transformation had superiority on maintaining spectral characteristics, but the result easily became block and blurred; PCA transformation maintained most detail texture and architectural feature of source imagery, but it couldn’t maintain detail spectral information. The research shows that, these three indexes can be taken as the evaluation criterion of remote sensing image fusion, they can also be used as good reference for many applications.