Robust Parameter Estimation in Computer Vision
SIAM Review
Removing camera shake from a single photograph
ACM SIGGRAPH 2006 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
ACM SIGGRAPH Asia 2009 papers
Image deblurring using inertial measurement sensors
ACM SIGGRAPH 2010 papers
Optical computing for fast light transport analysis
ACM SIGGRAPH Asia 2010 papers
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
Richardson-Lucy Deblurring for Scenes under a Projective Motion Path
IEEE Transactions on Pattern Analysis and Machine Intelligence
Blind deconvolution using a normalized sparsity measure
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Non-uniform Deblurring for Shaken Images
International Journal of Computer Vision
Space-Variant Restoration of Images Degraded by Camera Motion Blur
IEEE Transactions on Image Processing
Practical Poissonian-Gaussian Noise Modeling and Fitting for Single-Image Raw-Data
IEEE Transactions on Image Processing
Perceptually Optimized Coded Apertures for Defocus Deblurring
Computer Graphics Forum
Unnatural L0 Sparse Representation for Natural Image Deblurring
CVPR '13 Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition
Editorial: Foreword to the special section on advanced displays
Computers and Graphics
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Removing non-uniform blur caused by camera shaking is troublesome because of its high computational cost. We analyze the efficiency bottlenecks of a non-uniform deblurring algorithm and propose an efficient optical computation deblurring framework that implements the time-consuming and repeatedly required modules, i.e., non-uniform convolution and perspective warping, by light transportation. Specifically, the non-uniform convolution and perspective warping are optically computed by a hybrid system that is composed of an off-the-shelf projector and a camera mounted on a programmable motion platform. Benefitting from the high speed and parallelism of optical computation, our system has the potential to accelerate existing non-uniform motion deblurring algorithms significantly. To validate the effectiveness of the proposed approach, we also develop a prototype system that is incorporated into an iterative deblurring framework to effectively address the image blur of planar scenes that is caused by 3D camera rotation around the x-, y- and z-axes. The results show that the proposed approach has a high efficiency while obtaining a promising accuracy and has a high generalizability to more complex camera motions.