Data fusion: taking into account the modulation transfer function in ARSIS-based pansharpening methods

Abstract : Multispectral images provided by satellite have a poor spatial resolution while panchromatic images (PAN) exhibit a spatial resolution two or four times better. Data fusion is a mean to synthesize MS images at higher spatial resolution than original by exploiting the high spatial resolution of the PAN. This process is often called pan-sharpening. The synthesized multispectral images should be as close as possible to those that would have been acquired by the corresponding sensors if they had this high resolution. The methods based on the concept “Amélioration de la Résolution Spatiale par Injection de Structures” (ARSIS) concept are able to deliver synthesized images with good spectral quality but whose geometrical quality can still be enhanced. We propose to consider the characteristics of the sensor to improve the geometrical quality. We take explicitly into account the modulation transfer function (MTF) of the sensor in the fusion process. Though this study is limited in methods and data, we observe a better restitution of the geometry and an improvement in the majority of quality indices classically used in pan-sharpening. The communication also presents a means to assess the respect of the synthesis property from a MTF point of view.