ACM SIGGRAPH 2003 Papers
Removing camera shake from a single photograph
ACM SIGGRAPH 2006 Papers
Image deblurring with blurred/noisy image pairs
ACM SIGGRAPH 2007 papers
Image and depth from a conventional camera with a coded aperture
ACM SIGGRAPH 2007 papers
High-quality motion deblurring from a single image
ACM SIGGRAPH 2008 papers
How well do line drawings depict shape?
ACM SIGGRAPH 2009 papers
A benchmark for 3D mesh segmentation
ACM SIGGRAPH 2009 papers
ACM SIGGRAPH Asia 2009 papers
Image thumbnails that represent blur and noise
IEEE Transactions on Image Processing
Two-phase kernel estimation for robust motion deblurring
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Single image deblurring using motion density functions
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Automatic parameter selection for denoising algorithms using a no-reference measure of image content
IEEE Transactions on Image Processing
Perceptual models of viewpoint preference
ACM Transactions on Graphics (TOG)
Blind deconvolution using a normalized sparsity measure
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Learning a blind measure of perceptual image quality
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Efficient marginal likelihood optimization in blind deconvolution
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Blur kernel estimation using the radon transform
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Image information and visual quality
IEEE Transactions on Image Processing
Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering
IEEE Transactions on Image Processing
A No-Reference Image Blur Metric Based on the Cumulative Probability of Blur Detection (CPBD)
IEEE Transactions on Image Processing
Unsupervised feature learning framework for no-reference image quality assessment
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
A two-stage approach to blind spatially-varying motion deblurring
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
From learning models of natural image patches to whole image restoration
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
New measurements reveal weaknesses of image quality metrics in evaluating graphics artifacts
ACM Transactions on Graphics (TOG) - Proceedings of ACM SIGGRAPH Asia 2012
Perceptually Optimized Coded Apertures for Defocus Deblurring
Computer Graphics Forum
Blind correction of optical aberrations
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Blur-Kernel estimation from spectral irregularities
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Recording and playback of camera shake: benchmarking blind deconvolution with a real-world database
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VII
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Methods to undo the effects of motion blur are the subject of intense research, but evaluating and tuning these algorithms has traditionally required either user input or the availability of ground-truth images. We instead develop a metric for automatically predicting the perceptual quality of images produced by state-of-the-art deblurring algorithms. The metric is learned based on a massive user study, incorporates features that capture common deblurring artifacts, and does not require access to the original images (i.e., is "noreference"). We show that it better matches user-supplied rankings than previous approaches to measuring quality, and that in most cases it outperforms conventional full-reference image-similarity measures. We demonstrate applications of this metric to automatic selection of optimal algorithms and parameters, and to generation of fused images that combine multiple deblurring results.