Abstract: A system for identifying and tagging anomalies, such as images of dust and scratches, in a digital image so that they can be removed from the image. The invention implements a technique for detecting anomalies designed to minimize the number of false positives, i.e., non-anomalous portions of the image falsely identified as anomalies. The technique bases the initial first-pass identification of anomalous image regions on the difference between the gradient of the image at each of a set of grid points in the image and the mean of the gradient of the image at nearby points. Thus a region is identified as anomalous if original image pixel values in its immediate neighborhood are more variable than they are in a larger neighborhood. This technique greatly reduces (when compared to the prior art) the identification of false positives in noisy regions of the image, such as the leaves of a tree in daylight or a pebbly beach.