Spatial resolution is a key parameter of all kind of images. This is of particular importance in fields as, for example, medicine or remote sensing. The nominal resolution of a positron emission tomography (PET) or nuclear magnetic resonance (NMR) scanners are directly related to the size, number, and position of the detectors in the scanner ring. Also, the nominal spatial resolution of the remote sensing satellites is a well-known characteristic because it is directly related to the area in ground that represents a pixel in the detector. Nevertheless, in practice, the actual resolution of a medical scanner image or of an image obtained from a satellite is difficult to know precisely because it depends of many other factors. However, if we have two or more images of the same region of interest, obtained using similar or different instruments, it is possible to compare the relative resolution between them. In this paper we propose a wavelet-decomposition-based method for the determination of the relative resolution between two images of the same area. The method can be applied, in principle, to any kind of images. As example, we applied the method to pairs of remote sensing and medical images. In the case of remote sensing, we computed the relative resolution between SPOT-3, LANDSAT-5 and LANDSAT-7 panchromatic and multispectral images taken under similar as well as under very different conditions. In the case of medical imaging, we computed the relative resolution between a pair of simultaneously obtained PET and NMR images of the same object. On the other hand, if we know the true absolute resolution of one of the images of the pair, we can compute the resolution of the other. Thus, in the last part of this paper, we describe a spatial calibrator that we have designed and constructed to help compute the absolute resolution of a single remotely sensed image, presenting an example of its use. V