Satellite image fusion quality measurement by separating radiometric and geometric components

This paper focuses on quality assessment of fusion of multispectral (MS) images with high-resolution panchromatic (Pan) images. Since most existing quality assessments take the entire image into account simultaneously and generate some uncertainties, a novel and rather objective quality index has been proposed for image fusion. The index is comprised of geometric and radiometric parts. Both geometric and radiometric measurements are calculated using morphological algorithm applied on an edge image to create a mask which is used to separate high frequency regions from low frequency ones. The accuracy assessment is made using common existing criteria on geometric and radiometric segments and then a weighted sum is calculated to generate Radiometric and Geometric index (RG index). Several commonly used fusion algorithms such as IHS, modified IHS, PCA, Gram-Schmidt, Brovey Transform, Ehlers, High-Pass Modulation, Schowengerdt and UNB were applied on a very high resolution GeoEye and WorldView-2 images. In order to perform quality assessment, methods of Spectral Angle Mapper, Structural SIMilarity, Correlation Coefficients and Universal Quality Index for which the normalization were possible (for comparison purposes) were used. The utilized RG index showed that by separating spectral and spatial component quality measurement, the quality assessment is made on fused images in more distinct, explicit, accurate and objective manner.