Pansharpening Based on Fuzzy Logic and Edge Activity

Pansharpening technology aims to extract spatial information from a panchromatic (PAN) image and integrate it into a multispectral (MS) image to generate a high-spatial-resolution MS image. To overcome the problem of spatial and spectral distortion of traditional methods, this letter presents a pansharpening method based on fuzzy logic and edge activity. To obtain more accurate spatial details of source images, details extracted using the component substitution (CS) and multiresolution analysis (MRA) methods are fused via the proposed fuzzy logic algorithm. To preserve the edges of the fusion result, the edge maps of the source images are detected and fused based on the edge activity. The optimized detail maps are obtained by multiplying the fused details and edge maps, which are then injected into the upsampled MS (UPMS) image to obtain the final pansharpened image. Reduced- and full-scale experimental results on the Pleiades and IKONOS datasets demonstrate the effectiveness of our method compared with state-of-the-art pansharpening algorithms. Specifically, the proposed method improves the erreur relative global adimensionnelle de synthese (ERGAS) metrics by 9.0% and 11.1% compared to the second-best comparison approach on Pleiades and IKONOS, respectively.