Spatial consistency for full-scale assessment of pansharpening

Pansharpening usually refers to the fusion of a high spatial resolution panchromatic image with a low spatial resolution multispectral image. One of the most debated issue in this research field regards the quality assessment of fused products. The two exploited quality assessments are at reduced resolution and at full resolution. The former is an accurate procedure, but the main drawback is that it works on synthetic (with lower spatial resolutions) products. The latter is able to work at full resolution paying it with a reduced accuracy due to the absence of a ground-truth. In this work, we will focus on the assessment at full resolution by introducing a new measure of spatial consistency based on multivariate linear regression of the panchromatic image towards the multispectral bands. Simulations with an IKONOS dataset and six fusion methods show that the proposed spatial index is the ideal counterpart of Khan's spectral consistency index.