Research of Remote Sensing Image Fusion Method Based on the Contourlet Coefficients' Correlativity

In recent years, as an important branch of remote sensing image processing technology, remote sensing image fusion technologies have been widely applied, especially in the fields of resource exploration, environmental monitoring, region analysis and so on. The techniques can fuse different images from different sensors to an image which has complete information and accurate expression. Contourlet transform is comprehensively concerned in the discipline of remote sensing image processing for its excellent characteristics such as non-linear approximation, multi-resolution, time-frequency localization, multi-directional and anisotropy. In this paper, combining the directional characteristics of Contourlet transform, we analyze the correlativity attribute and propose a novel image fusion algorithm for remote sensing images based on Contourlet coefficients' correlativity. Firstly, we separately perform Contourlet transform on the intensity component of multi-spectral remote sensing image obtained by IHS transform, and panchromatic remote sensing image. Secondly, we propose the fusion priciple of self-adaption calculating fuesd weighting coefficients. Finally, the target image is obtained by reverse Contourlet transform and reverse IHS transform. Compared with the traditional fusion methods, our algorithm can enhance the spatial resolution of target image. Meanwhile, it preserves the spectral information of multi-spectral image well.