A method for predicting whether a test image (318) is sharp or blurred includes the steps of: training a sharpness classifier (316) to discriminate between sharp and blurred images, the sharpness classifier (316) being trained based on a set of training sharpness features (314) computed from a plurality of training images (306), the set of training sharpness features (314) for each training image (306) being computed by (i) resizing each training image (306) by a first resizing factor; (ii) identifying texture regions (408, 410) in the resized training image; and (iii) computing the set of sharpness features in the training image (412) from the identified texture regions; and applying the trained sharpness classifier (316) to the test image (318) to determine if the test image (318) is sharp or blurred based on a set of test sharpness features (322) computed from the test image (318), the set of test sharpness features (322) for each test image (318) being computed by (i) resizing the test image (318) by a second resizing factor that is different than the first resizing factor; (ii) identifying texture regions (408, 410) in the resized test image; and (iii) computing the set of sharpness features in the test image (412) from the identified texture regions.