Fetching the paper…
Reading the bibliography…
Given an image, we wish to produce an image of larger size with significantly more pixels and higher image quality.
R. Timofte, V. De, and L. Van Gool, “Anchored neighborhood regression for fast example-based super-resolution,” in IEEE International Conference on Computer Vision , Dec 2013, pp. 1920–1927
1927
Earlier work this paper cites.
H. Hou and H. Andrews, “Cubic splines for image interpolation and digital filtering,” IEEE Trans. on Acoustics, Speech and Signal Proc. , vol. 26, no. 6, pp. 508–517, 1978
1978
Earlier work this paper cites.
D. Marr and E. Hildreth, “Theory of edge detection,” Proceedings of the Royal Society of London B: Biological Sciences , vol. 207, no. 1167, pp. 187–217, 1980
1980
Earlier work this paper cites.
R. Keys, “Cubic convolution interpolation for digital image processing,” IEEE Trans. on Acoustics, Speech and Signal Proc. , vol. 29, no. 6, pp. 1153–1160, 1981
1981
Earlier work this paper cites.
Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, and L. D. Jackel, “Backpropagation applied to handwritten zip code recognition,” Neural computation , vol. 1, no. 4, pp. 541–551, 1989
1989
Earlier work this paper cites.
M. Irani and S. Peleg, “Improving resolution by image registration,” CVGIP: Graphical models and image processing , vol. 53, no. 3, pp. 231–239, 1991
1991
Earlier work this paper cites.
R. Zabih and J. Woodfill, “Non-parametric local transforms for computing visual correspondence,” in ECCV , 1994, pp. 151–158
1994
Earlier work this paper cites.
R. Barrett, M. W. Berry, T. F. Chan, J. Demmel, J. Donato, J. Dongarra, V. Eijkhout, R. Pozo, C. Romine, and H. Van der Vorst, Templates for the solution of linear systems: building blocks for iterative methods . SIAM, 1994
1994
Earlier work this paper cites.
C. Tomasi and R. Manduchi, “Bilateral filtering for gray and color images,” ICCV, Bombay, India , pp. 836–846, January 1998
1998
Earlier work this paper cites.
A. Polesel, G. Ramponi, V. J. Mathews et al. , “Image enhancement via adaptive unsharp masking,” IEEE Transactions on Image Processing , vol. 9, no. 3, pp. 505–510, 2000
2000
Earlier work this paper cites.
D. Martin, C. Fowlkes, D. Tal, and J. Malik, “A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics,” in ICCV , vol. 2. IEEE, 2001, pp. 416–423
2001
Earlier work this paper cites.
F. Durand and J. Dorsey, “Fast bilateral filtering for the display of high-dynamic-range images,” in ACM transactions on graphics (TOG) , vol. 21, no. 3. ACM, 2002, pp. 257–266
2002
Earlier work this paper cites.
X. Feng and P. Milanfar, “Multiscale principal components analysis for image local orientation estimation,” Proceedings of the 36th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA , November 2002
2002
Earlier work this paper cites.
S. C. Park, M. K. Park, and M. G. Kang, “Super-resolution image reconstruction: a technical overview,” IEEE Signal Processing Magazine , vol. 20, no. 3, pp. 21–36, 2003
2003
Earlier work this paper cites.
H. Chang, D.-Y. Yeung, and Y. Xiong, “Super-resolution through neighbor embedding,” in CVPR . IEEE, 2004
2004
Earlier work this paper cites.
A. Buades, B. Coll, and J. M. Morel, “A review of image denoising algorithms, with a new one,” Multiscale Modeling and Simulation (SIAM interdisciplinary journal) , vol. 4, no. 2, pp. 490–530, 2005
2005
Earlier work this paper cites.
M. Aharon, M. Elad, and A. Bruckstein, “The K-SVD: An algorithm for designing of overcomplete dictionaries for sparse representation,” IEEE Transactions on Signal Processing , vol. 54, no. 11, pp. 4311–4322, November 2006
2006
Earlier work this paper cites.
H. Takeda, S. Farsiu, and P. Milanfar, “Kernel regression for image processing and reconstruction,” IEEE Trans. on Image Proc. , vol. 16, no. 2, pp. 349–366, February 2007
2007
Earlier work this paper cites.
K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, “Image denoising by sparse 3-D transform-domain collaborative filtering,” IEEE Trans. on Image Proc. , vol. 16, no. 8, pp. 2080–2095, August 2007
2007
Cited alongside, same era.
J. Yang, J. Wright, T. Huang, and Y. Ma, “Image super-resolution as sparse representation of raw image patches,” in IEEE Conference on Computer Vision and Pattern Recognition , June 2008, pp. 1–8
2008
Cited alongside, same era.
B. Zhang and J. P. Allebach, “Adaptive bilateral filter for sharpness enhancement and noise removal,” IEEE Transactions on Image Processing , vol. 17, no. 5, pp. 664–678, 2008
2008
Cited alongside, same era.
H. Takeda, P. Milanfar, M. Protter, and M. Elad, “Super-resolution without explicit subpixel motion estimation,” IEEE Transactions on Image Processing , vol. 18, no. 9, pp. 1958–1975, September 2009
2009
Cited alongside, same era.
L. He, H. Qi, and R. Zaretzki, “Beta process joint dictionary learning for coupled feature spaces with application to single image super-resolution,” in IEEE Conference on Computer Vision and Pattern Recognition , 2013, pp. 345–352
2013
Later among the works it cites.
R. R. Makwana and N. D. Mehta, “Single image super-resolution via iterative back projection based Canny edge detection and a Gabor filter prior,” International Journal of Soft Computing & Engineering , 2013
2013
Later among the works it cites.
R. Timofte, V. De Smet, and L. Van Gool, “A+: Adjusted anchored neighborhood regression for fast super-resolution,” in ACCV , 2014, pp. 111–126
2014
Later among the works it cites.
Y. Romano, M. Protter, and M. Elad, “Single image interpolation via adaptive nonlocal sparsity-based modeling,” IEEE Trans. on Image Processing , vol. 23, no. 7, pp. 3085–3098, 2014
2014
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
W. Dong, L. Zhang, G. Shi, and X. Wu, “Nonlocal back-projection for adaptive image enlargement,” in IEEE International Conference on Image Processing . IEEE, 2009, pp. 349–352
2009
Cited alongside, same era.
K. He, J. Sun, and X. Tang, “Guided image filtering,” in ECCV , 2010, pp. 1–14
2010
Cited alongside, same era.
S.-C. Jeong and B. C. Song, “Training-based super-resolution algorithm using k-means clustering and detail enhancement,” in European Signal Processing Conference . IEEE, 2010, pp. 1791–1795
2010
Cited alongside, same era.
H. Song, X. He, W. Chen, and Y. Sun, “An improved iterative back-projection algorithm for video super-resolution reconstruction,” in Proceedings of the Symposium on Photonics and Optoelectronic . IEEE, 2010, pp. 1–4
2010
Cited alongside, same era.
J. Yang, J. Wright, T. S. Huang, and Y. Ma, “Image super-resolution via sparse representation,” IEEE Transactions on Image Processing , vol. 19, no. 11, pp. 2861–2873, 2010
2010
Cited alongside, same era.
D. Zoran and Y. Weiss, “From learning models of natural image patches to whole image restoration,” in ICCV . IEEE, 2011, pp. 479–486
2011
Cited alongside, same era.
R. Zeyde, M. Elad, and M. Protter, “On single image scale-up using sparse-representations,” in Curves and Surfaces . Springer, 2012, pp. 711–730
2012
Cited alongside, same era.
J. Yang, Z. Wang, Z. Lin, S. Cohen, and T. Huang, “Coupled dictionary training for image super-resolution,” IEEE Transactions on Image Processing , vol. 21, no. 8, pp. 3467–3478, 2012
2012
Cited alongside, same era.
T. Peleg and M. Elad, “A statistical prediction model based on sparse representations for single image super-resolution,” IEEE Transactions on Image Processing , vol. 23, no. 6, pp. 2569–2582, 2014
2014
Later among the works it cites.
C. Dong, C. C. Loy, K. He, and X. Tang, “Learning a deep convolutional network for image super-resolution,” in ECCV , 2014, pp. 184–199
2014
Later among the works it cites.
H. Talebi and P. Milanfar, “Nonlocal image editing,” IEEE Transactions on Image Processing , vol. 23, no. 10, pp. 4460–4473, 2014
2014
Later among the works it cites.
H. Talebi and P. Milanfar, “Global image denoising,” IEEE Transactions on Image Processing , vol. 23, no. 2, pp. 755–768, 2014
2014
Later among the works it cites.
A. Kheradmand and P. Milanfar, “A general framework for regularized, similarity-based image restoration,” IEEE Transactions on Image Processing , vol. 23, no. 12, pp. 5136–5151, 2014
2014
Later among the works it cites.
D. Dai, R. Timofte, and L. Van Gool, “Jointly optimized regressors for image super-resolution,” in Computer Graphics Forum , vol. 34, no. 2. Wiley Online Library, 2015, pp. 95–104
2015
Later among the works it cites.
A. Kheradmand and P. Milanfar, “Nonlinear structure-aware image sharpening with difference of smoothing operators,” Frontiers in ICT , vol. 2, p. 22, 2015
2015
Later among the works it cites.
X. Liu, G. Cheung, and X. Wu, “Joint denoising and contrast enhancement of images using graph laplacian operator,” in IEEE International Conference on Acoustics, Speech and Signal Processing . IEEE, 2015, pp. 2274–2278
2015
Later among the works it cites.
Y. Romano and M. Elad, “Patch-disagreement as a way to improve K-SVD denoising,” in IEEE International Conference on Acoustics, Speech and Signal Processing . IEEE, 2015, pp. 1280–1284
2015
Later among the works it cites.
——, “Boosting of image denoising algorithms,” SIAM Journal on Imaging Sciences , vol. 8, no. 2, pp. 1187–1219, 2015
2015
Later among the works it cites.
D. Chao, C. C. Loy, H. Kaiming, and T. Xiaoou, “Image super-resolution using deep convolutional networks,” IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 38, no. 2, pp. 295–307, Feb 2016
2016
Closest in time.
V. Papyan and M. Elad, “Multi-scale patch-based image restoration,” IEEE Transactions on Image Processing , vol. 25, no. 1, pp. 249–261, 2016
2016
Closest in time.
G. Ghimpeteanu, T. Batard, M. Bertalmio, and S. Levine, “A decomposition framework for image denoising algorithms,” IEEE Transactions on Image Processing , vol. 25, no. 1, pp. 388–399, 2016
2016
Closest in time.