Learning to Deblur

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 38, Issue 7, 2016, Pages 1439-1451

  Schuler, Christian J ^a   Hirsch, Michael ^a   Harmeling, Stefan ^a,b   Scholkopf, Bernhard ^a  

^a MAX PLANCK INSTITUTE FOR INTELLIGENT SYSTEMS   (Germany)

^b HEINRICH HEINE UNIVERSITY   (Germany)

Author keywords

machine learning; neural networks; Sharpening and deblurring

Indexed keywords

ARTIFICIAL INTELLIGENCE; CONVOLUTION; LEARNING SYSTEMS; NEURAL NETWORKS;

BLIND DECONVOLUTION; BLIND IMAGE DECONVOLUTION; COMPETITIVE PERFORMANCE; IMAGE DE CONVOLUTIONS; LAYERED ARCHITECTURE; LEARNING-BASED APPROACH; NEURAL NETWORK LEARNING; SHARPENING AND DEBLURRING;

LEARNING ALGORITHMS;

EID: 84976521325     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2015.2481418     Document Type: Article

References (36)

1. R. Fergus, B. Singh, A. Hertzmann, S. T. Roweis, W. T. Freeman, "Removing camera shake from a single photograph," ACM Trans. Graph., vol. 25, no. 3, pp. 787-794, 2006.
2. S. Cho and S. Lee, "Fast motion deblurring," ACM Trans. Graph., vol. 28, no. 5, p. 145, 2009.
3. L. Xu and J. Jia, "Two-phase kernel estimation for robust motion deblurring," in Proc. 11th Eur. Conf. Comput. Vis., 2010, pp. 157-170.
4. L. Bottou and P. Gallinari, "A framework for the cooperation of learning algorithms," in Proc. Adv. Neural Inf. Process. Syst., 1991, pp. 781-788.
5. D. Wipf and H. Zhang, "Revisiting Bayesian blind deconvolution," ArXiv e-prints, 2013.
6. M. Egmont-Petersen, D. de Ridder, H. Handels, "Image processing with neural networks a review," Pattern Recog., vol. 35, no. 10, pp. 2279-2301, 2002.
7. D. De Ridder, R. P. Duin, M. Egmont-Petersen, L. J. van Vliet, P. W. Verbeek, "Nonlinear image processing using artificial neural networks," Adv. Imag. Elect. Phys., vol. 126, pp. 352-450, 2003.
8. I. Aizenberg, D. Paliy, C. Moraga, J. Astola, "Blur identification using neural network for image restoration," in Proc. 9th Int. Conf. Comput. Intell. Theory Appl., 2006, vol. 38, pp. 441-455.
9. C. Khare and K. K. Nagwanshi, "Image restoration in neural network domain using back propagation network approach," Int. J. Comput. Inf. Syst., vol. 2, no. 5, pp. 25-31, 2011.
10. C. M. Cho and H. S. Don, "Blur identification and image restoration using a multilayer neural network," in Proc. IEEE Int. Joint Conf. Neural Netw., 1991, pp. 2558-2563.
11. J. E. Tansley, M. J. Oldfield, D. J. MacKay, "Neural network image deconvolution," in Maximum Entropy and Bayesian Methods, ser. Fundamental Theories of Physics. New York, NY, USA: Springer, 1996, pp. 319-325.
12. R. J. Steriti and M. A. Fiddy, "Blind deconvolution of images by use of neural networks," Optics Lett., vol. 19, no. 8, pp. 575-577, 1994.
13. C. J. Schuler, H. C. Burger, S. Harmeling, B. Schlkopf, "A machine learning approach for non-blind image deconvolution," in Proc. IEEE Conf. Comput. Vis. Pattern Recog., 2013, pp. 1067-1074.
14. L. Xu, J. S. Ren, C. Liu, J. Jia, "Deep convolutional neural network for image deconvolution," in Proc. Adv. Neural Inf. Process. Syst., 2014, pp. 1790-1798.
15. J. Sun, W. Cao, Z. Xu, J. Ponce, "Learning a convolutional neural network for non-uniform motion blur removal," ArXiv e-prints, 2015.
16. Z. Hu, J.-B. Huang, M.-H. Yang, "Single image deblurring with adaptive dictionary learning," in Proc. IEEE Int. Conf. Image Process., 2010, pp. 1169-1172.
17. U. Schmidt, C. Rother, S. Nowozin, J. Jancsary, S. Roth, "Discriminative non-blind deblurring," in Proc. IEEE Conf. Comput. Vis. Pattern Recog., 2013, pp. 604-611.
18. M. D. Zeiler, D. Krishnan, G. W. Taylor, R. Fergus, "Deconvolutional networks," in Proc. IEEE Conf. Comput. Vis. Pattern Recog., 2010, pp. 2528-2535.
19. M. D. Zeiler, G. W. Taylor, R. Fergus, "Adaptive deconvolutional networks for mid and high level feature learning," in Proc. IEEE Int. Conf. Comput. Vis., 2011, pp. 2018-2025.
20. L. Xu, S. Zheng, J. Jia, "Unnatural l0 sparse representation for natural image deblurring," in Proc. IEEE Conf. Comput. Vis. Pattern Recog., 2013, pp. 1107-1114.
21. J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, L. Fei-fei, "ImageNet: A large-scale hierarchical image database," in Proc. IEEE Conf. Comput. Vis. Pattern Recog., 2009, pp. 248-255.
22. C. E. Rasmussen and C. K. I. Williams, Gaussian Processes for Machine Learning. West Sussex, England: Univ. Press Group Limited, 2006.
23. M. D. Zeiler, "ADADELTA: An adaptive learning rate method," ArXiv e-prints, 2012.
24. D. Erhan, A. Courville, Y. Bengio, "Understanding representations learned in deep architectures," Univ de Montr-eal/DIRO, Montr-eal, QC, Canada, Tech. Rep. 1355, 2010.
25. Z. Hu and M.-H. Yang, "Good regions to deblur," in Proc. 12th Eur. Conf. Comput. Vis. 2012, pp. 59-72.
26. A. Levin, Y. Weiss, F. Durand, W. T. Freeman, "Understanding and evaluating blind deconvolution algorithms," in Proc. IEEE Conf. Comput. Vis. Pattern Recog., 2009, pp. 1964-1971.
27. L. Sun, S. Cho, J. Wang, J. Hays, "Edge-based blur kernel estimation using patch priors," in Proc. IEEE Int. Conf. Comput. Photography, 2013, pp. 1-8.
28. C. Wang, Y. Yue, F. Dong, Y. Tao, X. Ma, G. Clapworthy, H. Lin, X. Ye, "Nonedge-specific adaptive scheme for highly robust blind motion deblurring of natural images," IEEE Trans. Image Process., vol. 22, no. 3, pp. 884-897, Mar. 2013.
29. L. Zhong, S. Cho, D. Metaxas, S. Paris, J. Wang, "Handling noise in single image deblurring using directional filters," in Proc. IEEE Conf. Comput. Vis. Pattern Recog., 2013, pp. 612-619.
30. S. Harmeling, M. Hirsch, B. Schlkopf, "Space-variant singleimage blind deconvolution for removing camera shake," in Proc. Adv. Neural Inf. Process. Syst., 2010, pp. 829-837.
31. M. Hirsch, C. J. Schuler, S. Harmeling, B. Schlkopf, "Fast removal of non-uniform camera shake," in Proc. IEEE Int. Conf. Comput. Vis., 2011, pp. 463-470.
32. M. Hirsch, S. Sra, B. Schlkopf, S. Harmeling, "Efficient filter flow for space-variant multiframe blind deconvolution." in Proc. IEEE Conf. Comput. Vis. Pattern Recog., 2010, pp. 607-614.
33. A. Levin, Y. Weiss, F. Durand, W. T. Freeman, "Efficient marginal likelihood optimization in blind deconvolution," in Proc. IEEE Conf. Comput. Vis. Pattern Recog., 2011, pp. 2657-2664.
34. D. Krishnan, T. Tay, R. Fergus, "Blind deconvolution using a normalized sparsity measure," in Proc. IEEE Conf. Comput. Vis. Pattern Recog., 2011, pp. 233-240.
35. T. Michaeli and M. Irani, "Blind deblurring using internal patch recurrence," in Proc. IEEE Eur. Conf. Comput. Vis. 2014, pp. 783-798.
36. D. Zoran and Y. Weiss, "From learning models of natural image patches to whole image restoration," in Proc. IEEE Int. Conf. Comput. Vis., 2011, pp. 479-486.