An improved IHS fusion for high resolution remote sensing images

Abstract

Image fusion plays an important role in improving high resolution remote sensing images, as many Earth observation satellites provide both high-resolution panchromatic and multispectral images. To date, many image fusion techniques have been developed. Existing traditional image fusion techniques such as the intensity-hue-saturation (IHS) transform, wavelet transform and principal components analysis(PCA) methods may not be optimal for fusing the new generation commercial high-resolution satellite images such as IKONOS and Quick Bird. However, the available algorithms can hardly meet a satisfactory fusion requirement for high resolution remote sensing images. Among the existing fusion algorithms, the IHS technique is the most widely used one technique. But the color distortion of this technique is often obvious, especially when high resolution multispectral images are fused with its panchromatic images. This study presents a new fusion approach that integrates both IHS and histogram match techniques to reduce the color distortion of high resolution remote sensing fusion results. Different high resolution remote sensing images have been fused with this new approach. The result proves that the concept of the proposed improved IHS is promising, and it does significantly improve the fusion quality compared to conventional IHS transform fusion techniques.