We describe a new image fusion paradigm that provides an enhanced image from a set of source images that present regions with different spatial degradation patterns. The fusion procedure is based on the use of a new defocusing pixel-level measure. Such a measure is defined through a 1-D pseudo-Wigner distribution function (PWD) applied to nonoverlapping N-pixel window slices of the original image. The process is repeated to cover the full image size. By taking a low-resolution image as a reference image, which can be defined by blurring and averaging the two source images, a pixel-level distance measure of the defocus degree can be obtained from the PWD of each image. This procedure makes it possible to choose from a focusing point of view the in-focus pixels from each one of the given source images. The method is illustrated with different pairs of images of the same scene, which are partly focused and partly defocused in different regions. The image fusion approach that we propose here can work for any source of images available, and the comparison using evaluation measures such as mean square error or percentage of correct decisions shows that our framework can outperform the current approaches for the analyzed cases. One additional advantage of the present approach is its reduced computational cost when compared with other methods based on a full 2-D implementation of the PWD.