Robust identification of motion and out-of-focus blur parameters from blurred and noisy images
CVGIP: Graphical Models and Image Processing
Deconvolution of images and spectra (2nd ed.)
Deconvolution of images and spectra (2nd ed.)
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Limits on Super-Resolution and How to Break Them
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion Deblurring and Super-resolution from an Image Sequence
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Recovery of blurred video signals using iterative image restoration combined with motion estimation
ICIP '97 Proceedings of the 1997 International Conference on Image Processing (ICIP '97) 3-Volume Set-Volume 1 - Volume 1
Simultaneous image formation and motion blur restoration via multiple capture
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Two motion-blurred images are better than one
Pattern Recognition Letters - Special issue: In memoriam Azriel Rosenfeld
Image deblurring with blurred/noisy image pairs
ACM SIGGRAPH 2007 papers
ACM SIGGRAPH 2007 courses
Scanning Depth of Route Panorama Based on Stationary Blur
International Journal of Computer Vision
Progressive inter-scale and intra-scale non-blind image deconvolution
ACM SIGGRAPH 2008 papers
Depth from stationary blur with adaptive filtering
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part II
Non-blind image deconvolution with adaptive regularization
PCM'10 Proceedings of the 11th Pacific Rim conference on Advances in multimedia information processing: Part I
Velocity-dependent shutter sequences for motion deblurring
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part VI
Bayesian blind deconvolution from differently exposed image pairs
IEEE Transactions on Image Processing
Video temporal super-resolution based on self-similarity
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
Video deblurring and super-resolution technique for multiple moving objects
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part IV
High-quality non-blind image deconvolution with adaptive regularization
Journal of Visual Communication and Image Representation
Image deblurring with matrix regression and gradient evolution
Pattern Recognition
Image enhancement of low-light scenes with near-infrared flash images
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part I
High-quality image deblurring with panchromatic pixels
ACM Transactions on Graphics (TOG)
Computational plenoptic imaging
ACM SIGGRAPH 2012 Courses
Registration Based Non-uniform Motion Deblurring
Computer Graphics Forum
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
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Motion blur due to camera motion can significantly degrade the quality of an image. Since the path of the camera motion can be arbitrary, deblurring of motion blurred images is a hard problem. Previous methods to deal with this problem have included blind restoration of motion blurred images, optical correction using stabilized lenses, and special CMOS sensors that limit the exposure time in the presence of motion. In this paper, we exploit the fundamental tradeoff between spatial resolution and temporal resolution to construct a hybrid camera that can measure its own motion during image integration. The acquired motion information is used to compute a point spread function (PSF) that represents the path of the camera during integration. This PSF is then used to deblur the image. To verify the feasibility of hybrid imaging for motion deblurring, we have implemented a prototype hybrid camera. This prototype system was evaluated in different indoor and outdoor scenes using long exposures and complex camera motion paths. The results show that, with minimal resources, hybrid imaging outperforms previous approaches to the motion blur problem.