Fast classified pansharpening with spectral and spatial distortion optimization

This paper presents a fast method suitable for pansharpening of MS imagery. Key points of the novel method, which falls in the category of component substitution (CS) methods, are optimization of the intensity component, achieved through multivariate regression of Pan to MS, and adjustment of the modulus of the spatial detail vector to be injected, based on a minimization of spatial distortion. Spatial distortion is measured at full scale according to the QNR protocol on land cover classes defined by NDVI thresholding. Experiments carried out on IKONOS data demonstrate that results are competitive with those of the most advanced methods, with a computational complexity comparable with that of Brovey transform fusion, which is the baseline version of the proposed method.