Intensity-hue-saturation model based image fusion of SPOT-5 HRG1 data for crop identification

Image fusion can merge multi-source RS data outputting a better quality image. But the fusion model is dependent on the specific image type used, the specific temporal properties of the images, the specific land cover of the study area and what specific information to be extracted from the source images. SPOT-5 HRG1 image is a kind of new RS image at high spatial resolution that has been used in agricultural condition monitoring. In this study, SPOT-5 HRG1 multispectral and super mode panchromatic images were merged for soybean identification in Northeast China. Image fusions based on intensity-hue-saturation transformation (IHS) and Principal Component Analysis (PCA) were respectively done. The visual inspection and quantitative comparison of the two fusion images indicate that IHS model based image fusion of SPOT-5 HRG1 images was better for soybean identification than that of PCA model based.