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In this paper, the characteristics of multispectral (MS) and panchromatic (P) image fusion methods are investigated. Depending on the way spatial details are extracted from P, pansharpening methods can be broadly labeled into two main classes, corresponding to methods based on either component substitution (CS) or multiresolution analysis (MRA). Theoretical investigations and experimental results evidence that CS-based fusion is far less sensitive than MRA-based fusion to: 1) registration errors, i.e., spatial misalignments between MS and P images, possibly originated by cartographic projection and resampling of individual data sets; 2) aliasing occurring in MS bands and stemming from modulation transfer functions (MTF) of MS channels that are excessively broad for the sampling step. In order to assess the sensitiveness of methods, aliasing is simulated at degraded spatial scale by means of several MTF-shaped digital filters. Analogously, simulated misalignments, carried out at both full and degraded scale, evidence the quality-shift tradeoff of the two classes. MRA yields a slightly superior quality in the absence of aliasing/misalignments, but is more penalized than CS, whenever either aliasing or shifts between MS and P occur. Conversely, CS generally produces a slightly lower quality, but is intrinsically more aliasing/shift tolerant.