Fusion of IKONOS Satellite Imagery Using IHS Transform and Local Variation

Abstract

The intensity-hue-saturation (IHS) technique is a well-known merging approach for its computational efficiency and spatial definition holding. However, it results in color distortion particularly for the remote sensing images of IKONOS and QuickBird as some other fusion methods, such as principal component analysis, and Brovey transform. Although wavelet-based image fusion approaches can provide a better tradeoff between spatial and spectral quality, the fused images with these methods often have a spatial resolution that is less than that of the IHS-based algorithm. A remote sensing image fusion algorithm based on IHS transform and local variation and its modified approach with low computational complexity are proposed. Visual effect and quantity evaluation results show that the proposed simple algorithm outperforms the conventional image fusion methods in the spectral domain with the spatial quality similar to that of the undecimated wavelet transform-based scheme. The proposed modified method can obtain the similar spatial resolution of the merged image with the IHS-based fusion algorithm and the better spectral quality in the green vegetation areas.