Training classifiers for deblurring images

摘要

A classifier training system trains a classifier for evaluating image deblurring quality using a set of scored deblurred images. In some embodiments, the classifier training system trains the classifier based on a number of sub-images extracted from the scored deblurred images. An image deblurring system applies a number of different deblurring transformations to a given blurry reference image and uses the classifier trained by the classifier training system to evaluate deblurring quality, thereby finding a highest-quality deblurred image. In some embodiments, the classifier training system trains the classifier in the frequency domain, and the image deblurring system uses the classifier trained by the classifier training system to evaluate deblurring quality in the frequency domain. In some embodiments, the image deblurring system applies the different deblurring transformations iteratively.

主权项

1. A machine-readable non-transitory storage medium encoded with instructions that, when executed by a processor, cause the processor to perform a method comprising:
generating a plurality of perturbed deblurring kernels by perturbing a first deblurring kernel; applying each of the plurality of perturbed deblurring kernels to a blurry image to produce a plurality of deblurred images; determining a plurality of deblurring scores by applying a classifier to each of the plurality of deblurred images; selecting, using the plurality of deblurring scores, one of the plurality of perturbed deblurring kernels, as the selected deblurring kernel; applying a frequency domain transform to the blurry image; and applying the selected deblurring kernel to the blurry image to produce a deblurred image.