Pansharpening refers to the fusion process of inferring a high-resolution multispectral image from a high-resolution panchromatic image and a low-resolution multispectral one. In this paper we propose a new variational method for pansharpening which incorporates a nonlocal regularization term and two fidelity terms, one describing the relation between the panchromatic image and the highresolution spectral channels and the other one preserving the colors from the low-resolution modality. The nonlocal term is based on the image self-similarity principle applied to the panchromatic image. The existence and uniqueness of minimizer for the described functional is proved in a suitable space of weighted integrable functions. Although quite successful in terms of relative error, state-of-theart pansharpening methods introduce relevant color artifacts. These spectral distortions can be significantly reduced by involving the image self-similarity. Extensive comparisons with state-ofthe-art algorithms are performed. 1. Introduction. Many earth resource satellites, such as IKONOS, Landsat, QuickBird, and SPOT, provide continuously growing quantities of remote sensing images useful for a wide range of both scientific and everyday tasks. For example, satellite images are used to improve visual photointerpretation [54], digital-surface model extraction [45], and texture analysis [48]. Further applications are feature detection [24], land cover classification [33], estimating water depth [38], soil moisture content [43], vegetation mapping [21], and many military tasks such as mission planning, navigation, and targeting.Digital color images are usually represented by three color values at each pixel. Nevertheless, most common cameras use a CCD sensor device measuring a single color per pixel. The other two color values of each pixel must be interpolated from the neighboring pixels in the so-called demosaicking process. The selected configuration of the CCD sensor usually follows the CFA Bayer, where, out of a group of four pixels, two are green, one is red, and one is blue. Most satellites use a different acquisition system that decouples the acquisition of a panchromatic image at high spatial resolution from the acquisition of a multispectral