1. A method for processing an image comprising pixels, the method comprising: identifying anomalies in the image at a first anomaly size scale, comprising: subsampling a digital image by a subsample factor related to the first anomaly size scale, thereby generating a subsampled image having a lower resolution than the digital image in accordance with the subsample factor; smoothing the subsampled image to generate a smoothed image; determining a least-positive negated-second derivative for each pixel in the smoothed image; determining each pixel having a convex down curvature based on a least-positive negated-second derivative value for the respective pixel; joining each eight-neighbor connected pixels having convex down curvature to identify each initial anomaly area having only the first anomaly size scale, wherein, for each initial anomaly area, an internal pixel of the respective initial anomaly area represents a point of least curvature for the respective initial anomaly area; selecting one or more of the initial anomaly areas having only the first anomaly size scale and having strongest convex down curvatures based on a respective maximum least-positive negated-second derivative value at the respective internal pixel for each of the initial anomaly areas; extracting one or more classification features for each selected anomaly area having only the first anomaly size scale; and classifying the selected anomaly areas having only the first anomaly size scale based on the extracted one or more classification features; and performing the identifying the anomalies in the image for a plurality of different anomaly size scales.