Four methods for spatial component extraction used for SAR image fusion

When high-resolution optical multispectral image is used for SAR image fusion, its spatial component should be extracted first. There are two primary methods for spatial component extraction: principal component analysis (PCA) and intention-hue-saturation (IHS) transform. PCA method transforms the multispectral image into several noncorrelated and independent components and the first component (PC-1) represents the spatial component of the original multispectral image. IHS method transforms only three bands of the original multispectral image into three components of intention, hue and saturation. The spatial components extracted from the optical image respectively using these two methods are directly merged with the SAR image. The result suggests that the spatial component extracted by PCA enhances the spatial features of the SAR image better than that by IHS transform, but distorts the spectral properties of the SAR image compared with that by IHS method does. When the spatial components enhanced by maximum-minimum (0～255) linear stretch are used to fuse with the SAR image, they can both get better spatially enhanced SAR image but with more spectral distortion. But the enhanced spatial component by PCA still spatially enhances the SAR image better than that by IHS method, and the enhanced component by IHS method still preserve the spectral better than that by PCA method. Through the study four methods are proposed for spatial component extraction used for SAR image fusion.