A new fusion method of remote sensing images based on wavelet transform

This paper proposes a novel wavelet-based image fusion method that combines the selection and weighted average fusion rules for interpreting remote sensing images. When the local variance of source images is various greatly, the fusion coefficient of images is obtained by the selection rule, otherwise it will be acquired by the weighted average rule. The new fusion rule both preserves the source images´ detail and improves the algorithm stability. Experiment results demonstrate that the new fusion rule is effective.