1. A method of processing images, comprising: training an image classifier to obtain a trained classifier adapted to classify an image as being a stego-image or a non-stego-image, said training comprising: forming multiple prediction error sets from neighboring samples of a set of known images, a prediction error for each pixel of the error sets being formed by subtracting a predicted pixel value from an original value in a common frame; thresholding the formed prediction error sets, wherein the thresholding comprises: comparing the prediction error for each pixel of the error sets to a threshold value; and maintaining a prediction error value for each prediction error value that is less than the threshold value, the prediction error value being the difference between the predicted pixel value and the original value in the common frame; and training the image classifier using the thresholded prediction error sets.