Multi-spectral image fusion algorithm based on local correlation coefficient weighted IHS transformation

摘要

In traditional IHS transformation, the panchromatic image directly replaces the intensity component, spatial information of the panchromatic image is reserved. But it may cause severe spectral distortion at the same time. Enlightened by correlation coefficient of two images and its physical meaning, a novel IHS transformation image fusion algorithm is proposed. It's called local correlation coefficient weighted IHS transformation image fusion algorithm (LCCW-IHS). The weighted parameter is determined by the local correlation coefficient between the high-resolution panchromatic image and multi-spectral image's intensity component. Then the two images are fused and the new intensity component is generated. Finally the fusion image is obtained by inverse IHS transformation. This method furthest synthesized the region characteristics in the original images to be fused. Both the spectral characteristics of multi-spectral image and the high- resolution features of the panchromatic image are maintained. And the texture details are also enhanced. The experimental results of multi-spectral image fusion, analyzed by both subjective and objective evaluations, show the proposed algorithm is effective for image fusion.