1. A computer-implemented method, the method comprising: accessing a blurry image; applying a plurality of deblurring transformations to the blurry image to produce a plurality of deblurred images; computing scores for the plurality of deblurred images according to a quality of the deblurring; extracting, from each of the plurality of deblurred images, a plurality of sets of sub-images, each set of sub-images comprising a sub-image from each of the plurality of deblurred images corresponding to a same region in each of the plurality of deblurred images; computing a frequency domain transform of each sub-image in the plurality of sets of sub-images, producing a plurality of frequency domain sub-images; extracting, from each frequency domain sub-image, an image feature vector characterizing one or more visual aspects of the sub-image; training a classifier based on the plurality of image feature vectors and on the computed scores, the classifier taking as input one or more deblurred images in a frequency domain, and producing as output a score quantifying deblurring quality of each of the one or more deblurred images in the frequency domain; and storing the classifier.