Remote sensing image fusion based on multi-objective evolutionary algorithm

The purpose of fusion the multispectral (MS) and panchromatic (PAN) remote sensing images is to obtain high spatial resolution and quality of the PAN image as well as to preserve spectral information of the MS image. The parameter selection of fusion rule will directly affect the fusion result. In this paper, a new fusion method is presented based on multi-objective evolutionary algorithm (called SMS-EMOA). First, the MS image is converted from the RGB color space into the HSI (Hue-Saturation-Intensity) color space. Then, by applying Contourlet transform to the PAN image and the Intensity component of the MS image, the weighted model is used to fuse the sub-images, and the SMS-EMOA is adopted for optimal parameter selection. Finally, a fusion image is obtained by the inverse Contourlet and HSI transform. The experimental results show that the proposed fusion rule optimization method not only can gain the spatial resolution, but also can preserve the spectral information of the original MS image very well.