박사

Dynamic Scene Deblurring: New Models, Algorithms, and Analysis

김태현 2016년
논문상세정보
' Dynamic Scene Deblurring: New Models, Algorithms, and Analysis' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • 응용 물리
  • Blind deblurring
  • Dynamic Scenes deblurring
  • Exemplar
  • Kernel-parametrization
  • Motion segmentation
  • Non-uniform blur
  • Spatially varying blur
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
4,659 0

0.0%

' Dynamic Scene Deblurring: New Models, Algorithms, and Analysis' 의 참고문헌

  • Z. Hu, L. Xu, and M.-H. Yang, \Joint depth estimation and camera shake removal from single blurry image," in Computer Vision and Pattern Recognition, 2014.
  • Y.-W. Tai, X. Chen, S. Kim, S. J. Kim, F. Li, J. Yang, J. Yu, Y. Matsushita, and M. S. Brown, \Nonlinear camera response functions and image deblurring: Theoretical analysis and practice," IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013.
  • Y.-W. Tai, P. Tan, and M. S. Brown, \Richardson-lucy deblurring for scenes under a projective motion path," IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011.
  • Y.-W. Tai and S. Lin, \Motion-aware noise ltering for deblurring of noisy and blurry images," in Computer Vision and Pattern Recognition, 2012.
  • Y. Matsushita, E. Ofek, W. Ge, X. Tang, and H.-Y. Shum, \Full-frame video stabilization with motion inpainting," IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006.
  • Y. Li, S. B. Kang, N. Joshi, S. M. Seitz, and D. P. Huttenlocher, \Generating sharp panoramas from motion-blurred videos," in Computer Vision and Pattern Recognition, 2010.
  • Y. Hacohen, E. Shechtman, and D. Lischinski, \Deblurring by example using dense correspondence," in International Conference on Computer Vision, 2013.
  • Y. HaCohen, E. Shechtman, D. B. Goldman, and D. Lischinski, \Non-rigid dense correspondence with applications for image enhancement," ACM Trans- actions on Graphics, 2011.
  • Y. Boykov, O. Veksler, and R. Zabih, \Fast approximate energy minimization via graph cuts," IEEE Transactions on Pattern Analysis and Machine Intelli- gence, 2001.
  • X. Zhu, S. Cohen, S. Schiller, and P. Milanfar, \Estimating spatially varying defocus blur from a single image," IEEE Transactions on Image Processing, 2013.
  • V. Kolmogorov, \Convergent tree-reweighted message passing for energy minimization," IEEE Transactions on Pattern Analysis Machine Intelligence, 2006.
  • T. Portz, L. Zhang, and H. Jiang, \Optical ow in the presence of spatiallyvarying motion blur," in Computer Vision and Pattern Recognition, 2012.
  • T. Pock, L. Zebedin, and H. Bischof, TGV-Fusion. Springer, 2011.
  • T. Pock and A. Chambolle, \Diagonal preconditioning for rst order primaldual algorithms in convex optimization," in International Conference on Com- puter Vision, 2011.
  • T. H. Kim, H. S. Lee, and K. M. Lee, \Optical ow via locally adaptive fusion of complementary data costs," in International Conference on Computer Vision, 2013.
  • T. H. Kim, B. Ahn, and K. M. Lee, \Dynamic scene deblurring," in Interna- tional Conference on Computer Vision, 2013.
  • T. H. Kim and K. M. Lee, \Segmentation-free dynamic scene deblurring," in Computer Vision and Pattern Recognition, 2014.
  • T. H. Kim and K. M. Lee, \Generalized video deblurring for dynamic scenes," in Computer Vision and Pattern Recognition, 2015.
  • S. Zhuo and T. Sim, \Defocus map estimation from a single image," Pattern Recognition, 2011.
  • S. Osher and L. I. Rudin, \Feature-oriented image enhancement using shock lters," SIAM Journal on Numerical Analysis, 1990.
  • S. Harmeling, H. Michael, and B. Schoelkopf, \Space-variant single-image blind deconvolution for removing camera shake," in Advances in Neural Information Processing Systems, 2010.
  • S. Dai and Y. Wu, \Motion from blur," in Computer Vision and Pattern Recog- nition, 2008.
  • S. Cho, Y. Matsushita, and S. Lee, \Removing non-uniform motion blur from images," in International Conference on Computer Vision, 2007.
  • S. Cho, J. Wang, and S. Lee, \Video deblurring for hand-held cameras using patch-based synthesis," ACM Transactions on Graphics, 2012.
  • S. Cho, H. Cho, Y.-W. Tai, and S. Lee, \Registration based non-uniform motion deblurring," in Computer Graphics Forum, 2012.
  • S. Cho and S. Lee, \Fast motion deblurring," ACM Transactions on Graphics, 2009.
  • S. Bae and F. Durand, \Defocus magni cation," in Computer Graphics Forum, 2007.
  • R. Ranftl, S. Gehrig, T. Pock, and H. Bischof, \Pushing the limits of stereo using variational stereo estimation," in Intelligent Vehicles Symposium, 2012.
  • R. Ranftl, K. Bredies, and T. Pock, \Non-local total generalized variation for optical ow estimation," in European Conference on Computer Vision, 2014.
  • R. Kohler, M. Hirsch, B. Mohler, B. Scholkopf, and S. Harmeling, \Recording and playback of camera shake: Benchmarking blind deconvolution with a realworld database," in European Conference on Computer Vision, 2012.
  • R. Fergus, B. Singh, A. Hertzmann, S. T. Roweis, and W. T. Freeman, \Removing camera shake from a single photograph," ACM Transactions on Graphics, 2006.
  • Q. Shan, J. Jia, and A. Agarwala, \High-quality motion deblurring from a single image," ACM Transactions on Graphics, 2008.
  • P. Bhat, C. L. Zitnick, M. Cohen, and B. Curless, \Gradientshop: A gradientdomain optimization framework for image and video ltering," ACM Transac- tions on Graphics, 2010.
  • O. Whyte, J. Sivic, A. Zisserman, and J. Ponce, \Non-uniform deblurring for shaken images," in Computer Vision and Pattern Recognition, 2010.
  • O. Whyte, J. Sivic, A. Zisserman, and J. Ponce, \Non-uniform deblurring for shaken images," International Journal of Computer Vision, 2012.
  • N. Joshi, S. B. Kang, C. L. Zitnick, and R. Szeliski, \Image deblurring using inertial measurement sensors," ACM Transactions on Graphics, 2010.
  • N. Joshi, R. Szeliski, and D. Kriegman, \Psf estimation using sharp edge prediction," in Computer Vision and Pattern Recognition, 2008.
  • M. Z. Brown, D. Burschka, and G. D. Hager, \Advances in computational stereo," IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003.
  • M. Werlberger, T. Pock, and H. Bischof, \Motion estimation with non-local total variation regularization," in Computer Vision and Pattern Recognition, 2010.
  • M. Hirsch, C. J. Schuler, S. Harmeling, and B. Scholkopf, \Fast removal of non-uniform camera shake," in International Conference on Computer Vision, 2011.
  • L. Yuan, J. Sun, L. Quan, and H.-Y. Shum, \Image deblurring with blurred/noisy image pairs," ACM Transactions on Graphics, 2007.
  • L. Xu, S. Zheng, and J. Jia, \Unnatural l0 sparse representation for natural image deblurring," in Computer Vision and Pattern Recognition, 2013.
  • L. Xu, J. S. Ren, C. Liu, and J. Jia, \Deep convolutional neural network for image deconvolution," in Advances in Neural Information Processing Systems, 2014.
  • L. Xu, J. Jia, and Y. Matsushita, \Motion detail preserving optical ow estimation," IEEE Transactions on Pattern Analysis Machine Intelligence, 2012.
  • L. Xu and J. Jia, \Two-phase kernel estimation for robust motion deblurring," in European Conference on Computer Vision, 2010.
  • L. I. Rudin, S. Osher, and E. Fatemi, \Nonlinear total variation based noise removal algorithms," Physica D: Nonlinear Phenomena, 1992.
  • L. Bar, B. Berkels, M. Rumpf, and G. Sapiro, \A variational framework for simultaneous motion estimation and restoration of motion-blurred video," in Computer Vision and Pattern Recognition, 2007.
  • K. Schelten and S. Roth, \Localized image blur removal through non-parametric kernel estimation," in International Conference on Pattern Recognition, 2014.
  • K. Bredies, K. Kunisch, and T. Pock, \Total generalized variation," SIAM Jour- nal on Imaging Sciences, 2010.
  • J.-F. Cai, H. Ji, C. Liu, and Z. Shen, \Blind motion deblurring using multiple images," Journal of computational physics, 2009.
  • J. Wul and M. J. Black, \Modeling blurred video with layers," in European Conference on Computer Vision, 2014.
  • J. Sun, W. Cao, Z. Xu, and J. Ponce, \Learning a convolutional neural network for non-uniform motion blur removal," in Computer Vision and Pattern Recognition, 2015.
  • J. Shi, L. Xu, and J. Jia, \Just noticeable defocus blur detection and estimation," in Computer Vision and Pattern Recognition, 2015.
  • J. Pan, Z. Hu, Z. Su, and M.-H. Yang, \Deblurring text images via l0-regularized intensity and gradient prior," in Computer Vision and Pattern Recognition, 2014.
  • J. Hu, O. Gallo, K. Pulli, and X. Sun, \Hdr deghosting: How to deal with saturation ?" in Computer Vision and Pattern Recognition, 2013.
  • J. Chen, L. Yuan, C.-K. Tang, and L. Quan, \Robust dual motion deblurring," in Computer Vision and Pattern Recognition, 2008.
  • J. Braux-Zin, R. Dupont, and A. Bartoli, \A general dense image matching framework combining direct and feature-based costs," in International Confer- ence on Computer Vision, 2013.
  • H. W. Engl, M. Hanke, and A. Neubauer, Regularization of Inverse Problems. Springer, 1996.
  • H. S. Lee and K. M. Lee, \Dense 3d reconstruction from severely blurred images using a single moving camera," in Computer Vision and Pattern Recognition, 2013.
  • H. Ji and K. Wang, \A two-stage approach to blind spatially-varying motion deblurring," in Computer Vision and Pattern Recognition, 2012.
  • G. Gilboa, N. Sochen, and Y. Y. Zeevi, \Image enhancement and denoising by complex di usion processes," IEEE Transactions on Pattern Analysis Machine Intelligence, 2004.
  • F. Steinbrucker, T. Pock, and D. Cremers, \Advanced data terms for variational optic ow estimation," in Proceedings of International Workshop on Vision, Modeling, and Visualization, 2009.
  • F. Couzinie-Devy, J. Sun, K. Alahari, and J. Ponce, \Learning to estimate and remove non-uniform image blur," in Computer Vision and Pattern Recognition, 2013.
  • E. Kee, S. Paris, S. Chen, and J. Wang, \Modeling and removing spatiallyvarying optical blur," in International Conference on Computational Photogra- phy, 2011.
  • D. Krishnan, T. Tay, and R. Fergus, \Blind deconvolution using a normalized sparsity measure," in Computer Vision and Pattern Recognition, 2009.
  • D. Krishnan and R. Fergus, \Fast image deconvolution using hyper-laplacian priors," in Advances in Neural Information Processing Systems, 2009.
  • D. J. Butler, J. Wul , G. B. Stanley, and M. J. Black, \A naturalistic open source movie for optical ow evaluation," in European Conference on Computer Vision, 2012.
  • D. Ferstl, C. Reinbacher, R. Ranftl, M. Ruther, and H. Bischof, \Image guided depth upsampling using anisotropic total generalized variation," in Interna- tional Conference on Computer Vision, 2013.
  • C. Zach, T. Pock, and H. Bischof, \A duality based approach for realtime tv-l 1 optical ow," Pattern Recognition, 2007.
  • C. Vogel, S. Roth, and K. Schindler, \An evaluation of data costs for optical ow," Pattern recognition, 2013.
  • C. Rhemann, A. Hosni, M. Bleyer, C. Rother, and M. Gelautz, \Fast costvolume ltering for visual correspondence and beyond," in Computer Vision and Pattern Recognition, 2011.
  • C. Paramanand and A. N. Rajagopalan, \Non-uniform motion deblurring for bilayer scenes," in Computer Vision and Pattern Recognition, 2013.
  • C. Michelot, \A nite algorithm for nding the projection of a point onto the canonical simplex of rn," Journal of Optimization Theory and Applications, 1986.
  • C. J. Schuler, M. Hirsch, S. Harmeling, and B. Scholkopf, \Learning to deblur," IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015.
  • A. Wedel, T. Pock, C. Zach, H. Bischof, and D. Cremers, \An improved algorithm for tv-l 1 optical ow," Statistical and Geometrical Approaches to Visual Motion Analysis, 2009.
  • A. Levin, \Blind motion deblurring using image statistics," in Advances in Neural Information Processing Systems, 2006.
  • A. Levin, Y. Weiss, F. Durand, and W. T. Freeman, \Understanding and evaluating blind deconvolution algorithms," in Computer Vision and Pattern Recog- nition, 2009.
  • A. Levin, D. Lischinski, and Y. Weiss, \A closed form solution to natural image matting," IEEE Transactions Pattern Analysis Machine Intelligence, 2008.
  • A. Levin and Y. Weiss, \User assisted separation of re ections from a single image using a sparsity prior," IEEE Transactions Pattern Analysis Machine Intelligence, 2007.
  • A. Gupta, N. Joshi, L. Zitnick, M. Cohen, and B. Curless, \Single image deblurring using motion density functions," in European Conference on Computer Vision, 2010.
  • A. Chambolle and T. Pock, \A rst-order primal-dual algorithm for convex problems with applications to imaging," Journal of Mathematical Imaging and Vision, 2011.
  • A. Chakrabarti, T. Zickler, and W. T. Freeman, \Analyzing spatially-varying blur," in Computer Vision and Pattern Recognition, 2010.