Pansharpening regards the fusion of a high spatial resolution but low spectral resolution (panchromatic) image with a high spectral resolution but low spatial resolution (multispectral) image. The estimation, at reduced resolution, of injection coefficients through regression is a widespread and powerful approach. In this work, the problem of the estimation of the injection coefficients at full resolution for regression-based pansharpening approaches is studied. Multiple approaches (based on guess images or an iterative method) are proposed. These are assessed at reduced resolution by exploiting a real dataset acquired by the IKONOS sensor. The quantitative results clearly demonstrate the superiority of the proposed iterative method.
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