18.4.3.3 Single Image Super Resolution

Chapter Contents (Back)
Super Resolution. Single Image Super Resolution. Single Image. Learning: See also Learning, Neural Nets for Single Image Super Resolution. Clearly overlap with the main section and the blur sections. See also Document Quality Enhancement, Super Resolution Evaluation.

Koike, K.[Kazumasa],
Image processor which converts image with poor resolution into image with improved resolution,
US_Patent5,231,519, Jul 27, 1993
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Freeman, W.T.[William T.], Pasztor, E.C.[Egon C.],
Estimating scenes using statistical properties of images and scenes,
US_Patent6,263,103, Jul 17, 2001
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Salerno, E.,
Superresolution Capabilities of the Gerchberg Method in the Band-Pass Case: An Eigenvalue Analysis,
IJIST(9), No. 2-3, 1998, pp. 181-188. 9805
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Conchello, J.A.,
Superresolution and Convergence Properties of the Expectation-Maximization Algorithm for Maximum-Likelihood Deconvolution of Incoherent Images,
JOSA-A(15), No. 10, October 1998, pp. 2609-2619. 9810
BibRef

Cohen, B., Dinstein, I.,
Polyphase back-projection filtering for image resolution enhancement,
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Poulo, R.J.[Richard J.], Nguyen, V.X.[Vu X.], Bostrom, V.S.[Vareck S.], Gorman, W.L.[Walter L.],
Creating high resolution images,
US_Patent6,535,650, Mar 18, 2003
WWW Link. BibRef 0303

Pan, M.C.[Min-Cheng],
A novel blind super-resolution technique based on the improved Poisson maximum a posteriori algorithm,
IJIST(12), No. 6, 2002, pp. 239-246.
WWW Link. 0308
BibRef

Almansa, A.[Andrés], Durand, S.[Sylvain], Rougé, B.[Bernard],
Measuring and Improving Image Resolution by Adaptation of the Reciprocal Cell,
JMIV(21), No. 3, November 2004, pp. 235-279.
DOI Link 0410
BibRef

Narasimhan, S.G.[Srinivasa G.], Nayar, S.K.[Shree K.],
Enhancing Resolution Along Multiple Imaging Dimensions Using Assorted Pixels,
PAMI(27), No. 4, April 2005, pp. 518-530.
IEEE Abstract. 0501
BibRef
And: A2, A1:
Assorted Pixels: Multi-sampled Imaging with Structural Models,
ECCV02(IV: 636 ff.).
Springer DOI 0205
E.g. using the RGB sensors in a digital camera to enhance spatial resolution. BibRef

Gupta, M.[Mohit], Agrawal, A.[Amit], Veeraraghavan, A.[Ashok], Narasimhan, S.G.[Srinivasa G.],
Flexible Voxels for Motion-Aware Videography,
ECCV10(I: 100-114).
Springer DOI 1009
BibRef

Liu, D.Y.[Deng-Yu], Gu, J.W.[Jin-Wei], Hitomi, Y.[Yasunobu], Gupta, M.[Mohit], Mitsunaga, T.[Tomoo], Nayar, S.K.[Shree K.],
Efficient Space-Time Sampling with Pixel-Wise Coded Exposure for High-Speed Imaging,
PAMI(36), No. 2, February 2014, pp. 248-260.
IEEE DOI 1402
BibRef
Earlier: A3, A2, A4, A5, A6, Only:
Video from a single coded exposure photograph using a learned over-complete dictionary,
ICCV11(287-294).
IEEE DOI 1201
Sampling to get best of high resolution and video. CMOS image sensors for high speed videos. BibRef

Agrawal, A.[Amit], Gupta, M.[Mohit], Veeraraghavan, A.[Ashok], Narasimhan, S.G.[Srinivasa G.],
Optimal coded sampling for temporal super-resolution,
CVPR10(599-606).
IEEE DOI 1006
BibRef

Zhang, L.[Li], Vaddadi, S.[Sundeep], Jin, H.L.[Hai-Lin], Nayar, S.K.[Shree K.],
Multiple view image denoising,
CVPR09(1542-1549).
IEEE DOI 0906
Group similar patches from different views. BibRef

Yang, F., Lu, Y.M., Sbaiz, L., Vetterli, M.,
Bits From Photons: Oversampled Image Acquisition Using Binary Poisson Statistics,
IP(21), No. 4, April 2012, pp. 1421-1436.
IEEE DOI 1204
Each pixel in the sensor has a binary response BibRef

Jeon, B.W.[Bo-Won], Park, R.H.[Rae-Hong], Yang, S.J.[Seung-Joon],
Resolution Enhancement by Prediction of the High-Frequency Image Based on the Laplacian Pyramid,
JASP(2006), 2006, pp. 1-11.
WWW Link. 0603
BibRef

Prasad, S.[Sudhakar],
Digital superresolution and the generalized sampling theorem,
JOSA-A(24), No. 2, February 2007, pp. 311-325.
WWW Link. 0801
BibRef

Sawhney, H.S.[Harpreet S.], Guo, Y.L.[Yan-Lin], Kumar, R.[Rakesh], Hanna, K.J.[Keith J.], Bergen, J.R.[James R.],
Techniques and systems for developing high-resolution imagery,
US_Patent7,260,274, Aug 21, 2007
WWW Link. BibRef 0708

Baboulaz, L.[Loic], Dragotti, P.L.[Pier Luigi],
Exact Feature Extraction Using Finite Rate of Innovation Principles With an Application to Image Super-Resolution,
IP(18), No. 2, February 2009, pp. 281-298.
IEEE DOI 0901
BibRef
Earlier:
Local Feature Extraction for Image Super-Resolution,
ICIP07(V: 401-404).
IEEE DOI 0709
BibRef
Earlier:
Distributed Acquisition and Image Super-Resolution Based on Continuous Moments from Samples,
ICIP06(3309-3312).
IEEE DOI 0610
BibRef

Flaherty, F.A.[Francis A.],
Physically constrained Fourier transform deconvolution method,
JOSA-A(26), No. 5, May 2009, pp. 1191-1194.
WWW Link. 0905
FT for resolution enhancement. BibRef

Piles, M., Camps, A., Vall-llossera, M., Talone, M.,
Spatial-Resolution Enhancement of SMOS Data: A Deconvolution-Based Approach,
GeoRS(47), No. 7, July 2009, pp. 2182-2192.
IEEE DOI 0906
Soil Moisture and Ocean Salinity BibRef

Shen, M.M.[Min-Min], Wang, C.[Ci], Xue, P.[Ping], Lin, W.S.[Wei-Si],
Performance of reconstruction-based super-resolution with regularization,
JVCIR(21), No. 7, October 2010, pp. 640-650.
Elsevier DOI 1003
Super-resolution; Reconstruction-based algorithms; Magnification factor; Regularization; Performance bound; Optimal regularization parameter; Condition number; PSF BibRef

Han, F.[Fei], Fang, X.Z.[Xiang-Zhong], Wang, C.[Ci],
Blind Super-resolution for Single Image Reconstruction,
PSIVT10(399-403).
IEEE DOI 1011
BibRef

Song, H.Y.[Hai-Ying], Qing, L.B.[Lin-Bo], Wu, Y.Y.[Yuan-Yuan], He, X.H.[Xiao-Hai],
Adaptive regularization-based space-time super-resolution reconstruction,
SP:IC(28), No. 7, 2013, pp. 763-778.
Elsevier DOI 1307
Super-resolution BibRef

Sun, J., Sun, J., Xu, Z.B.[Zong-Ben], Shum, H.Y.[Heung-Yeung],
Gradient Profile Prior and Its Applications in Image Super-Resolution and Enhancement,
IP(20), No. 6, June 2011, pp. 1529-1542.
IEEE DOI 1106
BibRef

Sun, J.[Jian], Xu, Z.B.[Zong-Ben], Shum, H.Y.[Heung-Yeung],
Image super-resolution using gradient profile prior,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Ben-Ezra, M.[Moshe], Lin, Z.C.[Zhou-Chen], Wilburn, B.[Bennett], Zhang, W.[Wei],
Penrose Pixels for Super-Resolution,
PAMI(33), No. 7, July 2011, pp. 1370-1383.
IEEE DOI 1106
BibRef
Earlier: A1, A2, A3, Only:
Penrose Pixels Super-Resolution in the Detector Layout Domain,
ICCV07(1-8).
IEEE DOI 0710
Use a periodic pixel tiling, Penrose or biological retina. BibRef

Zhang, H.C.[Hai-Chao], Zhang, Y.N.[Yan-Ning], Li, H., Huang, T.S.[Thomas S.],
Generative Bayesian Image Super Resolution With Natural Image Prior,
IP(21), No. 9, September 2012, pp. 4054-4067.
IEEE DOI 1208
BibRef
And:
Bayesian image separation with natural image prior,
ICIP12(2097-2100).
IEEE DOI 1302
BibRef
Earlier:
Sparse representation based iterative incremental image deblurring,
ICIP09(1293-1296).
IEEE DOI 0911
BibRef

Zhang, H.C.[Hai-Chao], Yang, J.C.[Jian-Chao], Zhang, Y.N.[Yan-Ning], Huang, T.S.[Thomas S.],
Image and Video Restorations via Nonlocal Kernel Regression,
Cyber(43), No. 3, 2013, pp. 1035-1046.
IEEE DOI 1307
BibRef
Earlier:
Multi-scale Non-Local Kernel Regression for super resolution,
ICIP11(1353-1356).
IEEE DOI 1201
BibRef
Earlier:
Non-Local Kernel Regression for Image and Video Restoration,
ECCV10(III: 566-579).
Springer DOI 1009
image denoising; video signal processing; image deblurring; local structural regularity properties; video superresolution reconstruction BibRef

Guo, L.[Lv], Li, Y.[Yin], Yang, J.[Jie], Lu, L.[Li],
Exploration into Single Image Super-Resolution via Self Similarity by Sparse Representation,
IEICE(E93-D), No. 11, November 2010, pp. 3144-3148.
WWW Link. 1011
BibRef

Bouzari, H.[Hamed],
An improved regularization method for artifact rejection in image super-resolution,
SIViP(6), No. 1, March 2012, pp. 125-140.
WWW Link. 1203
BibRef

Lu, X.Q.[Xiao-Qiang], Zheng, X.T.[Xiang-Tao], Li, X.L.[Xue-Long],
Latent Semantic Minimal Hashing for Image Retrieval,
IP(26), No. 1, January 2017, pp. 355-368.
IEEE DOI 1612
feature extraction BibRef

Katsuki, T., Torii, A., Inoue, M.,
Posterior-Mean Super-Resolution With a Causal Gaussian Markov Random Field Prior,
IP(21), No. 7, July 2012, pp. 3182-3193.
IEEE DOI 1206
BibRef

Torii, A., Wakazono, Y., Murakami, H., Imiya, A.,
PDE Based Method for Superresolution of Gray-Level Images,
CAIP03(706-713).
Springer DOI 0311
BibRef

Yang, J.C.[Jian-Chao], Wang, Z., Lin, Z.[Zhe], Cohen, S.[Scott], Huang, T.,
Coupled Dictionary Training for Image Super-Resolution,
IP(21), No. 8, August 2012, pp. 3467-3478.
IEEE DOI 1208
BibRef

Yang, J.C.[Jian-Chao], Lin, Z.[Zhe], Cohen, S.[Scott],
Fast Image Super-Resolution Based on In-Place Example Regression,
CVPR13(1059-1066)
IEEE DOI 1309
image restoration BibRef

Camponez, M.O.[Marcelo Oliveira], Salles, E.O.T.[Evandro O. Teatini], Sarcinelli-Filho, M.[Mario],
Super-Resolution Image Reconstruction Using Nonparametric Bayesian INLA Approximation,
IP(21), No. 8, August 2012, pp. 3491-3501.
IEEE DOI 1208
BibRef
And:
DFT-based fast superresolution image reconstruction using INLA approximation,
ICIP12(2217-2220).
IEEE DOI 1302
BibRef

Liang, Y.[Yan], Yuen, P.C.[Pong C.], Lai, J.H.[Jian-Huang],
Image super-resolution by textural context constrained visual vocabulary,
SP:IC(27), No. 10, November 2012, pp. 1096-1108.
Elsevier DOI 1211
Similarity preserving; Visual vocabulary; Textural context; Super-resolution BibRef

Yang, S.Y.[Shu-Yuan], Wang, M.[Min], Sun, Y.[Yaxin], Sun, F.H.[Feng-Hua], Jiao, L.C.[Li-Cheng],
Compressive Sampling based Single-Image Super-resolution Reconstruction by dual-sparsity and Non-local Similarity Regularizer,
PRL(33), No. 9, 1 July 2012, pp. 1049-1059.
Elsevier DOI 1202
Single-Image Super-Resolution Reconstruction; Compressive sampling; Dual-sparsity; Non-local similarities; Patch-pixel-collaboration BibRef

Yang, S.Y.[Shu-Yuan], Wang, M.[Min], Chen, Y., Sun, Y.[Yaxin],
Single-Image Super-Resolution Reconstruction via Learned Geometric Dictionaries and Clustered Sparse Coding,
IP(21), No. 9, September 2012, pp. 4016-4028.
IEEE DOI 1208
BibRef

Pan, Z., Yu, J., Huang, H., Hu, S., Zhang, A., Ma, H., Sun, W.,
Super-Resolution Based on Compressive Sensing and Structural Self-Similarity for Remote Sensing Images,
GeoRS(51), No. 9, 2013, pp. 4864-4876.
IEEE DOI 1309
Databases BibRef

Xiong, Z., Xu, D., Sun, X., Wu, F.,
Example-Based Super-Resolution With Soft Information and Decision,
MultMed(15), No. 6, 2013, pp. 1458-1465.
IEEE DOI 1309
Factor graph BibRef

Xu, H.T.[Hong-Teng], Zhai, G.T.[Guang-Tao], Yang, X.K.[Xiao-Kang],
Single Image Super-resolution With Detail Enhancement Based on Local Fractal Analysis of Gradient,
CirSysVideo(23), No. 10, 2013, pp. 1740-1754.
IEEE DOI 1311
estimation theory BibRef

Xu, H.T.[Hong-Teng], Zhai, G.T.[Guang-Tao], Wu, X.L.[Xiao-Lin], Yang, X.K.[Xiao-Kang],
Generalized Equalization Model for Image Enhancement,
MultMed(16), No. 1, January 2014, pp. 68-82.
IEEE DOI 1402
computational complexity BibRef

Chen, X.X.[Xiao-Xuan], Qi, C.[Chun],
Low-Rank Neighbor Embedding for Single Image Super-Resolution,
SPLetters(21), No. 1, January 2014, pp. 79-82.
IEEE DOI 1402
image resolution BibRef

Zachevsky, I.[Ido], Zeevi, Y.Y.[Yehoshua Y.],
Single-Image Superresolution of Natural Stochastic Textures Based on Fractional Brownian Motion,
IP(23), No. 5, May 2014, pp. 2096-2108.
IEEE DOI 1405
BibRef
Earlier:
Single-image superresolution of self-similar textures,
ICIP13(952-956)
IEEE DOI 1402
Estimation. Brownian motion BibRef

Zachevsky, I.[Ido], Zeevi, Y.Y.[Yehoshua Y.],
Statistics of Natural Stochastic Textures and Their Application in Image Denoising,
IP(25), No. 5, May 2016, pp. 2130-2145.
IEEE DOI 1604
BibRef
Earlier:
Denoising of natural stochastic colored-textures based on fractional brownian motion model,
ICIP15(1065-1069)
IEEE DOI 1512
BibRef
Earlier:
Combining long-range dependencies with phase information in Natural Stochastic Texture enhancement,
ICIP14(4487-4491)
IEEE DOI 1502
Texture enhancement. Correlation Brownian motion. BibRef

Purkait, P., Pal, N.R., Chanda, B.,
A Fuzzy-Rule-Based Approach for Single Frame Super Resolution,
IP(23), No. 5, May 2014, pp. 2277-2290.
IEEE DOI 1405
fuzzy systems BibRef

Peleg, T., Elad, M.,
A Statistical Prediction Model Based on Sparse Representations for Single Image Super-Resolution,
IP(23), No. 6, June 2014, pp. 2569-2582.
IEEE DOI 1406
Dictionaries BibRef

Zhou, F.[Fei], Yuan, T.R.[Ting-Rong], Yang, W.M.[Wen-Ming], Liao, Q.M.[Qing-Min],
Single-Image Super-Resolution Based on Compact KPCA Coding and Kernel Regression,
SPLetters(22), No. 3, March 2015, pp. 336-340.
IEEE DOI 1410
BibRef
And: A2, A3, A1, A4:
Single image super-resolution via sparse KPCA and regression,
ICIP14(2130-2134)
IEEE DOI 1502
Dictionaries BibRef

Yang, W.M.[Wen-Ming], Yuan, T.R.[Ting-Rong], Wang, W.[Wei], Zhou, F.[Fei], Liao, Q.M.[Qing-Min],
Single-Image Super-Resolution by Subdictionary Coding and Kernel Regression,
SMCS(47), No. 9, September 2017, pp. 2478-2488.
IEEE DOI 1708
Dictionaries, Encoding, Image coding, Image reconstruction, Image resolution, Interpolation, Kernel, Kernel regression, nonlinear mapping, sparse representation, subdictionary, super-resolution, (SR) BibRef

Tian, Y.P.[Ya-Peng], Zhou, F.[Fei], Yang, W.M.[Wen-Ming], Shang, X.S.[Xue-Sen], Liao, Q.M.[Qing-Min],
Anchored neighborhood regression based single image super-resolution from self-examples,
ICIP16(2827-2831)
IEEE DOI 1610
Dictionaries BibRef

Yang, F., Xie, D., Jia, H., Chen, R., Xiang, G., Gao, W.,
Structure preserving single image super-resolution,
ICIP16(1409-1413)
IEEE DOI 1610
Data integration BibRef

Yang, W.M.[Wen-Ming], Tian, Y., Zhou, F.[Fei], Liao, Q.M.[Qing-Min], Chen, H., Zheng, C.,
Consistent Coding Scheme for Single-Image Super-Resolution Via Independent Dictionaries,
MultMed(18), No. 3, March 2016, pp. 313-325.
IEEE DOI 1603
Dictionaries BibRef

Zhou, F.[Fei], Liao, Q.M.[Qing-Min],
Single-frame image super-resolution inspired by perceptual criteria,
IET-IPR(9), No. 1, 2015, pp. 1-11.
DOI Link 1502
image resolution BibRef

Bevilacqua, M.[Marco], Roumy, A.[Aline], Guillemot, C.[Christine], Morel, M.L.A.[Marie-Line Alberi],
Single-Image Super-Resolution via Linear Mapping of Interpolated Self-Examples,
IP(23), No. 12, December 2014, pp. 5334-5347.
IEEE DOI 1412
BibRef
Earlier:
Low-Complexity Single-Image Super-Resolution based on Nonnegative Neighbor Embedding,
BMVC12(135).
DOI Link 1301
image resolution BibRef

Feng, W.[Wensen], Lei, H.[Hong],
Single-image super-resolution with total generalised variation and Shearlet regularisations,
IET-IPR(8), No. 12, 2014, pp. 833-845.
DOI Link 1412
BibRef
And: Erratum: IET-IPR(9), No. 4, 2015, pp. 346-346.
DOI Link 1505
approximation theory BibRef

Bareja, M.N.[Milan N.], Modi, C.K.[Chintan K.],
An Improved Iterative Back Projection Based Single Image Super Resolution Approach,
IJIG(14), No. 04, 2014, pp. 1450015.
DOI Link 1412
BibRef

Lu, J.[Jian], Sun, Y.[Yi],
Context-aware single image super-resolution using sparse representation and cross-scale similarity,
SP:IC(32), No. 1, 2015, pp. 40-53.
Elsevier DOI 1503
Super-resolution BibRef

Cheng, M.[Ming], Wang, C.[Cheng], Li, J.,
Single-image super-resolution in RGB space via group sparse representation,
IET-IPR(9), No. 6, 2015, pp. 461-467.
DOI Link 1507
compressed sensing BibRef

Lowe, T.,
Improving image clarity using local feature dimension,
IET-IPR(9), No. 7, 2015, pp. 553-559.
DOI Link 1506
feature extraction BibRef

Peng, J.L.[Jia-Lin], Hon, B.Y.C.[Benny Y. C.], Kong, D.X.[De-Xing],
A structural low rank regularization method for single image super-resolution,
MVA(26), No. 7-8, November 2015, pp. 991-1005.
Springer DOI 1511
BibRef

karimi, N.[Naser], Amindavar, H.[Hamidreza], Kirlin, R.L.[Rodney Lynn], Rajabi, A.[Ahad],
Blind single-image super resolution based on compressive sensing,
JVCIR(33), No. 1, 2015, pp. 94-103.
Elsevier DOI 1512
Blind single-image super resolution BibRef

Hung, K.W.[Kwok-Wai], Siu, W.C.[Wan-Chi],
Single-image super-resolution using iterative Wiener filter based on nonlocal means,
SP:IC(39, Part A), No. 1, 2015, pp. 26-45.
Elsevier DOI 1512
Super-resolution reconstruction BibRef

Yu, S.[Soohwan], Kang, W.[Wonseok], Ko, S.Y.[Seung-Yong], Paik, J.[Joonki],
Single image super-resolution using locally adaptive multiple linear regression,
JOSA-A(32), No. 12, December 2015, pp. 2264-2275.
DOI Link 1601
Image processing; Image reconstruction-restoration; Superresolution BibRef

Jun, J.H.[Jae-Hee], Choi, J.H.[Ji-Hoon], Kim, J.O.[Jong-Ok],
Middle-Frequency Based Refinement for Image Super-Resolution,
IEICE(E99-D), No. 1, January 2016, pp. 300-304.
WWW Link. 1601
BibRef

Xian, Y.[Yang], Tian, Y.L.[Ying-Li],
Single image super-resolution via internal gradient similarity,
JVCIR(35), No. 1, 2016, pp. 91-102.
Elsevier DOI 1602
BibRef
Earlier:
Robust internal exemplar-based image enhancement,
ICIP15(2379-2383)
IEEE DOI 1512
Image super-resolution. exemplar-based BibRef

Tian, Y.L.[Ying-Li], Xian, Y.[Yang],
Resolution enhancement in single depth map and aligned image,
WACV16(1-9)
IEEE DOI 1606
Cameras BibRef

Xian, Y.[Yang], Yang, X.D.[Xiao-Dong], Tian, Y.L.[Ying-Li],
Hybrid Example-Based Single Image Super-Resolution,
ISVC15(II: 3-15).
Springer DOI 1601
BibRef

Zhang, Y.B.[Yong-Bing], Zhang, Y.L.[Yu-Lun], Zhang, J.[Jian], Dai, Q.H.[Qiong-Hai],
CCR: Clustering and Collaborative Representation for Fast Single Image Super-Resolution,
MultMed(18), No. 3, March 2016, pp. 405-417.
IEEE DOI 1603
Clustering algorithms BibRef

Zhang, Y.B.[Yong-Bing], Zhang, Y.L.[Yu-Lun], Zhang, J.[Jian], Xu, D.[Dong], Fu, Y.[Yun], Wang, Y.S.[Yi-Sen], Ji, X.Y.[Xiang-Yang], Dai, Q.H.[Qiong-Hai],
Collaborative Representation Cascade for Single-Image Super-Resolution,
SMCS(49), No. 5, May 2019, pp. 845-860.
IEEE DOI 1904
Feature extraction, Principal component analysis, Image reconstruction, Dictionaries, Image resolution, super-resolution BibRef

Zhang, X., Liu, Q., Li, X., Zhou, Y., Zhang, C.,
Non-local feature back-projection for image super-resolution,
IET-IPR(10), No. 5, 2016, pp. 398-408.
DOI Link 1604
image reconstruction BibRef

López-Rubio, E.[Ezequiel],
Superresolution from a Single Noisy Image by the Median Filter Transform,
SIIMS(9), No. 1, 2016, pp. 82-115.
DOI Link 1604
BibRef

Yoo, S.B.[Seok Bong], Choi, K.[Kyuha], Jeon, Y.W.[Young Woo], Ra, J.B.[Jong Beom],
Texture enhancement for improving single-image super-resolution performance,
SP:IC(46), No. 1, 2016, pp. 29-39.
Elsevier DOI 1606
Texture enhancement BibRef

Zhao, N., Wei, Q., Basarab, A., Dobigeon, N., Kouamé, D., Tourneret, J.Y.,
Fast Single Image Super-Resolution Using a New Analytical Solution for L_2- L_2 Problems,
IP(25), No. 8, August 2016, pp. 3683-3697.
IEEE DOI 1608
Convolution BibRef

Wei, X., Dragotti, P.L.,
FRESH: FRI-Based Single-Image Super-Resolution Algorithm,
IP(25), No. 8, August 2016, pp. 3723-3735.
IEEE DOI 1608
channel bank filters BibRef

Sandeep, P., Jacob, T.,
Single Image Super-Resolution Using a Joint GMM Method,
IP(25), No. 9, September 2016, pp. 4233-4244.
IEEE DOI 1609
Gaussian processes BibRef

Anver, J.[Jesna], Parambil, A.[Abdulla],
Single-image super-resolution using kernel recursive least squares,
SIViP(10), No. 8, November 2016, pp. 1551-1558.
WWW Link. 1610
BibRef

Anver, J.[Jesna], Parambil, A.[Abdulla],
Single-image super-resolution using online kernel adaptive filters,
IET-IPR(13), No. 11, 19 September 2019, pp. 1846-1852.
DOI Link 1909
BibRef

Deng, L.J., Guo, W., Huang, T.Z.,
Single-Image Super-Resolution via an Iterative Reproducing Kernel Hilbert Space Method,
CirSysVideo(26), No. 11, November 2016, pp. 2001-2014.
IEEE DOI 1609
Hilbert space BibRef

Jiang, J.J.[Jun-Jun], Ma, X., Chen, C.[Chen], Lu, T., Wang, Z.[Zheng], Ma, J.Y.[Jia-Yi],
Single Image Super-Resolution via Locally Regularized Anchored Neighborhood Regression and Nonlocal Means,
MultMed(19), No. 1, January 2017, pp. 15-26.
IEEE DOI 1612
Dictionaries BibRef

Zeng, K., Yu, J., Wang, R., Li, C., Tao, D.,
Coupled Deep Autoencoder for Single Image Super-Resolution,
Cyber(47), No. 1, January 2017, pp. 27-37.
IEEE DOI 1612
Dictionaries BibRef

Haris, M.[Muhammad], Widyanto, M.R.[M. Rahmat], Nobuhara, H.[Hajime],
First-order derivative-based super-resolution,
SIViP(11), No. 1, January 2017, pp. 1-8.
WWW Link. 1702
BibRef

Haris, M., Shakhnarovich, G., Ukita, N.,
Deep Back-Projection Networks for Super-Resolution,
CVPR18(1664-1673)
IEEE DOI 1812
Image reconstruction, Feature extraction, Task analysis, Training, Computer architecture, Spatial resolution BibRef

Ahmadi, K.[Kaveh], Salari, E.[Ezzatollah],
Single-image super resolution using evolutionary sparse coding technique,
IET-IPR(11), No. 1, January 2017, pp. 13-21.
DOI Link 1703
See also Small dim object tracking using a multi objective particle swarm optimisation technique. BibRef

Choi, J.S.[Jae-Seok], Kim, M.C.[Mun-Churl],
Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings,
IP(26), No. 3, March 2017, pp. 1300-1314.
IEEE DOI 1703
image resolution BibRef

Choi, J.S.[Jae-Seok], Kim, M.C.[Mun-Churl],
Single Image Super-Resolution Using Lightweight CNN with Maxout Units,
ACCV18(VI:471-487).
Springer DOI 1906
BibRef

Choi, J.S.[Jae-Seok], Bae, S.H.[Sung-Ho], Kim, M.C.[Mun-Churl],
Single image super-resolution based on self-examples using context-dependent subpatches,
ICIP15(2835-2839)
IEEE DOI 1512
Lloyd-Max quantization BibRef

Jebadurai, J.[Jebaveerasingh], Peter, J.D.[J Dinesh],
SK-SVR: Sigmoid kernel support vector regression based in-scale single image super-resolution,
PRL(94), No. 1, 2017, pp. 144-153.
Elsevier DOI 1708
Single, image, SR BibRef

Lee, H.J.[Hui Jung], Choi, D.Y.[Dong-Yoon], Lim, K.W.[Kyoung Won], Song, B.C.[Byung Cheol],
A Single Image Super-Resolution Algorithm Using Non-Local-Mean Self-Similarity and Noise-Robust Saliency Map,
IEICE(E100-D), No. 7, July 2017, pp. 1463-1474.
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Han, Y.L.[Yu-Lan], Zhao, Y.P.[Yong-Ping], Yu, H.F.[Hai-Feng],
Adaptive regularised L_2-boosting on clustered sparse coefficients for single image super-resolution,
IET-CV(11), No. 7, October 2017, pp. 517-529.
DOI Link 1709
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Gong, W.G.[Wei-Guo], Yi, Q.[Qiane], Tang, Y.[Yongliang], Li, W.H.[Wei-Hong],
Multi-layer strategy and reconstruction model with low rank and local rank regularizations for single image super-resolution,
SP:IC(57), No. 1, 2017, pp. 197-210.
Elsevier DOI 1709
Single image super-resolution BibRef

Laghrib, A.[Amine], Hakim, A.[Abdelilah], Raghay, S.[Said],
An iterative image super-resolution approach based on Bregman distance,
SP:IC(58), No. 1, 2017, pp. 24-34.
Elsevier DOI 1710
Super-resolution BibRef

Zhao, J.W.[Jian-Wei], Hu, H.P.[He-Ping], Zhou, Z.H.[Zheng-Hua], Cao, F.L.[Fei-Long],
Super-resolution reconstruction: Using non-local structure similarity and edge sharpness dictionary,
IET-IPR(11), No. 12, Decmeber 2017, pp. 1254-1264.
DOI Link 1712
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Bhowmik, A., Shit, S., Seelamantula, C.S.,
Training-Free, Single-Image Super-Resolution Using a Dynamic Convolutional Network,
SPLetters(25), No. 1, January 2018, pp. 85-89.
IEEE DOI 1801
Gaussian processes, Laplace equations, image representation, image resolution, Gaussian pyramids, HR ? LR generative model, super-resolution (SR) BibRef

Cruz, C., Mehta, R., Katkovnik, V., Egiazarian, K.O.,
Single Image Super-Resolution Based on Wiener Filter in Similarity Domain,
IP(27), No. 3, March 2018, pp. 1376-1389.
IEEE DOI 1801
Dictionaries, Image edge detection, Image reconstruction, Image resolution, Signal resolution, Training, Training data, sparsity BibRef

Jung, C.[Cheolkon], Ke, P.[Peng], Sun, Z.[Zengzeng], Gu, A.[Aiguo],
A fast deconvolution-based approach for single-image super-resolution with GPU acceleration,
RealTimeIP(14), No. 2, February 2018, pp. 501-512.
WWW Link. 1804
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Deng, X.,
Enhancing Image Quality via Style Transfer for Single Image Super-Resolution,
SPLetters(25), No. 4, April 2018, pp. 571-575.
IEEE DOI 1804
image enhancement, image reconstruction, image resolution, GAN based SISR method, SRGAN, generative adversarial network, style transfer BibRef

Huang, S., Sun, J., Yang, Y., Fang, Y., Lin, P., Que, Y.,
Robust Single-Image Super-Resolution Based on Adaptive Edge-Preserving Smoothing Regularization,
IP(27), No. 6, June 2018, pp. 2650-2663.
IEEE DOI 1804
edge detection, filtering theory, image denoising, image enhancement, image reconstruction, image resolution, regularization BibRef

Chang, K., Ding, P.L.K., Li, B.,
Single Image Super Resolution Using Joint Regularization,
SPLetters(25), No. 4, April 2018, pp. 596-600.
IEEE DOI 1804
DH-HEMTs, Estimation, Feature extraction, Image reconstruction, Image resolution, Signal processing algorithms, Training, total variation (TV) BibRef

Zhang, Y.F.[Yun-Feng], Fan, Q.L.[Qing-Lan], Bao, F.X.[Fang-Xun], Liu, Y.F.[Yi-Fang], Zhang, C.M.[Cai-Ming],
Single-Image Super-Resolution Based on Rational Fractal Interpolation,
IP(27), No. 8, August 2018, pp. 3782-3797.
IEEE DOI 1806
approximation theory, fractals, image reconstruction, image resolution, image texture, interpolation, LR input image, scaling factor BibRef

Yao, X.X.[Xun-Xiang], Wu, Q.A.[Qi-Ang], Zhang, P.[Peng], Bao, F.X.[Fang-Xun],
Adaptive rational fractal interpolation function for image super-resolution via local fractal analysis,
IVC(82), 2019, pp. 39-49.
Elsevier DOI 1904
Image super-resolution, Texture detail, Fractal function, Vertical scaling factor, Fractal dimension BibRef

Liu, Y.[Yuan], Wang, Y.C.[Yuan-Cheng], Li, N.[Nan], Cheng, X.[Xu], Zhang, Y.F.[Yi-Feng], Huang, Y.M.[Yong-Ming], Lu, G.J.[Guo-Jun],
An Attention-Based Approach for Single Image Super Resolution,
ICPR18(2777-2784)
IEEE DOI 1812
Image resolution, Image reconstruction, Convolution, Feature extraction, Task analysis, Image segmentation BibRef

Chen, H.G.[Hong-Gang], He, X.H.[Xiao-Hai], Qing, L.[Linbo], Teng, Q.[Qizhi], Ren, C.[Chao],
SGCRSR: Sequential gradient constrained regression for single image super-resolution,
SP:IC(66), 2018, pp. 1-18.
Elsevier DOI 1806
Image super-resolution, Sequential regression, Gradient constraint, Combination BibRef

Zhang, C.P.[Chao-Peng], Liu, W.R.[Wei-Rong], Liu, J.[Jie], Liu, C.R.[Chao-Rong], Shi, C.H.[Chang-Hong],
Sparse representation and adaptive mixed samples regression for single image super-resolution,
SP:IC(67), 2018, pp. 79-89.
Elsevier DOI 1808
Adaptive mixed samples, Ridge regression, Sparse representation, Super-resolution BibRef

Haut, J.M., Fernandez-Beltran, R., Paoletti, M.E., Plaza, J., Plaza, A., Pla, F.,
A New Deep Generative Network for Unsupervised Remote Sensing Single-Image Super-Resolution,
GeoRS(56), No. 11, November 2018, pp. 6792-6810.
IEEE DOI 1811
Spatial resolution, Remote sensing, Image reconstruction, Data models, Imaging, Training, super-resolution (SR) BibRef

Tao, Y.[Yu], Muller, J.P.[Jan-Peter],
Super-Resolution Restoration of MISR Images Using the UCL MAGiGAN System,
RS(11), No. 1, 2018, pp. xx-yy.
DOI Link 1901
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Zhang, Q.L.[Qing-Lin], Chen, B.L.[Bing-Ling], Lu, X.[Xuan], Xia, Q.Q.[Qiao-Qiao],
Super-resolution of single multi-color image with guided filter,
JVCIR(58), 2019, pp. 277-284.
Elsevier DOI 1901
Super-resolution, Multi-color image, Guided filter, Chromatic channel BibRef

Yuan, Y.[Yuan], Yang, X.M.[Xiao-Min], Wu, W.[Wei], Li, H.[Hu], Liu, Y.G.[Yi-Guang], Liu, K.[Kai],
A fast single-image super-resolution method implemented with CUDA,
RealTimeIP(16), No. 1, February 2019, pp. 81-97.
Springer DOI 1902
BibRef

Yang, X., Mei, H., Zhang, J., Xu, K., Yin, B., Zhang, Q., Wei, X.,
DRFN: Deep Recurrent Fusion Network for Single-Image Super-Resolution With Large Factors,
MultMed(21), No. 2, February 2019, pp. 328-337.
IEEE DOI 1902
Feature extraction, Image reconstruction, Convolution, Image resolution, Interpolation, Databases, Visualization, large factors BibRef

Zheng, H.B.[Hong-Bo], Ren, L.Y.[Liu-Yan], Ling-Ling, K.[Ke], Qin, X.[Xujia], Zhang, M.Y.[Mei-Yu],
Single image fast deblurring algorithm based on hyper-Laplacian model,
IET-IPR(13), No. 3, February 2019, pp. 483-490.
DOI Link 1903
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Abiantun, R.[Ramzi], Juefei-Xu, F.[Felix], Prabhu, U.[Utsav], Savvides, M.[Marios],
SSR2: Sparse signal recovery for single-image super-resolution on faces with extreme low resolutions,
PR(90), 2019, pp. 308-324.
Elsevier DOI 1903
Sparse signal recovery (SSR), Single-image super-resolution (SSR), Extreme low resolution BibRef

Zhu, S.[Shujin], Li, Y.[Yuehua],
Single image super-resolution under multi-frame method,
SIViP(13), No. 2, March 2019, pp. 331-339.
WWW Link. 1904
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Shao, W.Z.[Wen-Ze], Ge, Q.[Qi], Wang, L.Q.[Li-Qian], Lin, Y.Z.[Yun-Zhi], Deng, H.S.[Hai-Song], Li, H.B.[Hai-Bo],
Nonparametric Blind Super-Resolution Using Adaptive Heavy-Tailed Priors,
JMIV(61), No. 6, July 2019, pp. 885-917.
Springer DOI 1907
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Yang, J.X.[Jing-Xiang], Zhao, Y.Q.A.[Yong-Qi-Ang], Chan, J.C.W.[Jonathan Cheung-Wai], Xiao, L.[Liang],
A Multi-Scale Wavelet 3D-CNN for Hyperspectral Image Super-Resolution,
RS(11), No. 13, 2019, pp. xx-yy.
DOI Link 1907
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Gu, J.[Jun], Sun, X.[Xian], Zhang, Y.[Yue], Fu, K.[Kun], Wang, L.[Lei],
Deep Residual Squeeze and Excitation Network for Remote Sensing Image Super-Resolution,
RS(11), No. 15, 2019, pp. xx-yy.
DOI Link 1908
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Dian, R., Li, S.,
Hyperspectral Image Super-Resolution via Subspace-Based Low Tensor Multi-Rank Regularization,
IP(28), No. 10, October 2019, pp. 5135-5146.
IEEE DOI 1909
Spatial resolution, Correlation, Sparse matrices, Hyperspectral imaging, Optimization, Super-resolution, image fusion BibRef

Song, L.F.[Ling-Fei], Fu, Y.[Ying], Huang, H.[Hua], Chen, Y.[Yufeng],
Fast HSI super resolution using linear regression,
IET-IPR(13), No. 10, 22 August 2019, pp. 1671-1679.
DOI Link 1909
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Li, X.G.[Xiao-Guang], Sun, X.[Xu], Lam, K.M.[Kin Man], Zhuo, L.[Li], Li, J.[Jiafeng], Dong, N.[Ning],
Deep-network based method for joint image deblocking and super-resolution,
IET-IPR(13), No. 10, 22 August 2019, pp. 1636-1647.
DOI Link 1909
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Feng, X.B.[Xu-Bin], Su, X.Q.[Xiu-Qin], Shen, J.[Junge], Jin, H.[Humin],
Single Space Object Image Denoising and Super-Resolution Reconstructing Using Deep Convolutional Networks,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909
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Fu, B.[Bo], Li, Y.[Yi], Wang, X.H.[Xiang-Hai], Ren, Y.G.[Yong-Gong],
Image super-resolution using TV priori guided convolutional network,
PRL(125), 2019, pp. 780-784.
Elsevier DOI 1909
Image super-resolution, TV priori, Non-local regression, Convolutional network BibRef

Brifman, A., Romano, Y., Elad, M.[Michael],
Unified Single-Image and Video Super-Resolution via Denoising Algorithms,
IP(28), No. 12, December 2019, pp. 6063-6076.
IEEE DOI 1909
BibRef
Earlier:
Turning a denoiser into a super-resolver using plug and play priors,
ICIP16(1404-1408)
IEEE DOI 1610
Noise reduction, Spatial resolution, Inverse problems, Noise measurement, Task analysis, Mathematical model, ADMM. Degradation BibRef

Pan, Z.X.[Zong-Xu], Ma, W.[Wen], Guo, J.Y.[Jia-Yi], Lei, B.[Bin],
Super-Resolution of Single Remote Sensing Image Based on Residual Dense Backprojection Networks,
GeoRS(57), No. 10, October 2019, pp. 7918-7933.
IEEE DOI 1910
feature extraction, geophysical image processing, image classification, image reconstruction, image resolution, single image super-resolution (SISR) BibRef

Ma, W.[Wen], Pan, Z.X.[Zong-Xu], Yuan, F.[Feng], Lei, B.[Bin],
Super-Resolution of Remote Sensing Images via a Dense Residual Generative Adversarial Network,
RS(11), No. 21, 2019, pp. xx-yy.
DOI Link 1911
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Shamsolmoali, P.[Pourya], Li, X.F.[Xiao-Fang], Wang, R.[Ruili],
Single image resolution enhancement by efficient dilated densely connected residual network,
SP:IC(79), 2019, pp. 13-23.
Elsevier DOI 1911
Image super-resolution, Dilated convolution, Dense network, Optimization BibRef


Hatvani, J., Basarab, A., Michetti, J., Gyöngy, M., Kouamé, D.,
Tensor-Factorization-Based 3d Single Image Super-Resolution with Semi-Blind Point Spread Function Estimation,
ICIP19(2871-2875)
IEEE DOI 1910
image enhancement, 3D super-resolution, semi-blind deconvolution, 3D computed tomography BibRef

Wu, G., Zhao, L., Wang, W., Zeng, L., Chen, J.,
PRED: A Parallel Network for Handling Multiple Degradations via Single Model in Single Image Super-Resolution,
ICIP19(2881-2885)
IEEE DOI 1910
SISR, multiple degradation, CNN, PRED BibRef

Bai, F.R.[Fu-Rui], Lu, W.[Wen], Zha, L.[Lin], Sun, X.P.[Xiao-Peng], Guan, R.X.[Ruo-Xuan],
Non-Local Hierarchical Residual Network for Single Image Super-Resolution,
ICIP19(2821-2825)
IEEE DOI 1910
Super resolution, CNNs, non-local module, hierarchical residual structure BibRef

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Proximal Splitting Networks for Image Restoration,
ICIAR19(I:3-17).
Springer DOI 1909
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Pendurkar, S.[Sumedh], Banerjee, B.[Biplab], Saha, S.[Sudipan], Bovolo, F.[Francesca],
Single Image Super-Resolution for Optical Satellite Scenes Using Deep Deconvolutional Network,
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Springer DOI 1909
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Supervised Deep Kriging for Single-Image Super-Resolution,
GCPR18(638-649).
Springer DOI 1905
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Huang, J.[Jie], Zhu, P.F.[Peng-Fei], Geng, M.[Mingrui], Ran, J.[Jiewen], Zhou, X.[Xingguang], Xing, C.[Chen], Wan, P.F.[Peng-Fei], Ji, X.Y.[Xiang-Yang],
Range Scaling Global U-Net for Perceptual Image Enhancement on Mobile Devices,
PerceptualRest18(V:230-242).
Springer DOI 1905
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de Stoutz, E.[Etienne], Ignatov, A.[Andrey], Kobyshev, N.[Nikolay], Timofte, R.[Radu], Van Gool, L.J.[Luc J.],
Fast Perceptual Image Enhancement,
PerceptualRest18(V:260-275).
Springer DOI 1905
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Gondal, M.W.[Muhammad Waleed], Schölkopf, B.[Bernhard], Hirsch, M.[Michael],
The Unreasonable Effectiveness of Texture Transfer for Single Image Super-Resolution,
PerceptualRest18(V:80-97).
Springer DOI 1905
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Vu, T.[Thang], Luu, T.M.[Tung M.], Yoo, C.D.[Chang D.],
Perception-Enhanced Image Super-Resolution via Relativistic Generative Adversarial Networks,
PerceptualRest18(V:98-113).
Springer DOI 1905
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Vasu, S.[Subeesh], Madam, N.T.[Nimisha Thekke], Rajagopalan, A.N.,
Analyzing Perception-Distortion Tradeoff Using Enhanced Perceptual Super-Resolution Network,
PerceptualRest18(V:114-131).
Springer DOI 1905
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Purohit, K.[Kuldeep], Mandal, S.[Srimanta], Rajagopalan, A.N.,
Scale-Recurrent Multi-residual Dense Network for Image Super-Resolution,
PerceptualRest18(V:132-149).
Springer DOI 1905
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Li, Y.W.[Ya-Wei], Agustsson, E.[Eirikur], Gu, S.H.[Shu-Hang], Timofte, R.[Radu], Van Gool, L.J.[Luc J.],
CARN: Convolutional Anchored Regression Network for Fast and Accurate Single Image Super-Resolution,
PerceptualRest18(V:166-181).
Springer DOI 1905
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Gu, S.H.[Shu-Hang], Sang, N.[Nong], Ma, F.[Fan],
Fast image super resolution via local regression,
ICPR12(3128-3131).
WWW Link. 1302
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Luo, X.T.[Xiao-Tong], Chen, R.[Rong], Xie, Y.[Yuan], Qu, Y.[Yanyun], Li, C.[Cuihua],
Bi-GANs-ST for Perceptual Image Super-Resolution,
PerceptualRest18(V:20-34).
Springer DOI 1905
BibRef

Shi, Z.[Zhan], Chen, C.[Chang], Xiong, Z.W.[Zhi-Wei], Liu, D.[Dong], Zha, Z.J.[Zheng-Jun], Wu, F.[Feng],
Deep Residual Attention Network for Spectral Image Super-Resolution,
PerceptualRest18(V:214-229).
Springer DOI 1905
BibRef

Wu, X.Y.[Xian-Yu], Li, X.J.[Xiao-Jie], He, J.[Jia], Wu, X.[Xi], Mumtaz, I.[Imran],
Generative Adversarial Networks with Enhanced Symmetric Residual Units for Single Image Super-Resolution,
MMMod19(I:483-494).
Springer DOI 1901
BibRef

Lui, V.[Vincent], Geeves, J.[Jonathon], Yii, W.[Winston], Drummond, T.W.[Tom W.],
Efficient Subpixel Refinement with Symbolic Linear Predictors,
CVPR18(8165-8173)
IEEE DOI 1812
Transmission line matrix methods, Matrices, Cost function, Discrete cosine transforms, Minimization BibRef

Duan, P., Ming, A., Kang, X., Yao, C.,
A New Single Image Super-resolution Method Using SIMK-based Classification and ISRM Technique,
ICPR18(3043-3048)
IEEE DOI 1812
Linear regression, Image resolution, Kernel, Complexity theory, Testing, Image reconstruction, Probabilistic logic, regression BibRef

Cheng, X.[Xi], Li, X.[Xiang], Yang, J.[Jian], Tai, Y.[Ying],
SESR: Single Image Super Resolution with Recursive Squeeze and Excitation Networks,
ICPR18(147-152)
IEEE DOI 1812
Computational modeling, Image reconstruction, Convolution, Training, Task analysis, Spatial resolution, super resolution, recursive networks BibRef

Chen, R., Qu, Y., Zeng, K., Guo, J., Li, C., Xie, Y.,
Persistent Memory Residual Network for Single Image Super Resolution,
Restoration18(922-9227)
IEEE DOI 1812
Degradation, Image resolution, Logic gates, Training, Image restoration, Convolution, Image reconstruction BibRef

Sharma, M., Mukhopadhyay, R., Upadhyay, A., Koundinya, S., Shukla, A., Chaudhury, S.,
IRGUN : Improved Residue Based Gradual Up-Scaling Network for Single Image Super Resolution,
Restoration18(947-94709)
IEEE DOI 1812
Image resolution, Image reconstruction, Convolution, Training, Interpolation, Image color analysis BibRef

Wang, Y., Perazzi, F., McWilliams, B., Sorkine-Hornung, A., Sorkine-Hornung, O., Schroers, C.,
A Fully Progressive Approach to Single-Image Super-Resolution,
Restoration18(977-97709)
IEEE DOI 1812
Training, Image resolution, Image reconstruction, Generative adversarial networks, Computer architecture, Generators BibRef

Park, S.J.[Seong-Jin], Son, H.[Hyeongseok], Cho, S.[Sunghyun], Hong, K.S.[Ki-Sang], Lee, S.Y.[Seung-Yong],
SRFeat: Single Image Super-Resolution with Feature Discrimination,
ECCV18(XVI: 455-471).
Springer DOI 1810
BibRef

Moshtaghpour, A., Jacques, L.,
Multilevel Illumination Coding for Fourier Transform Interferometry in Fluorescence Spectroscopy,
ICIP18(1433-1437)
IEEE DOI 1809
Interferometric procedure for acquiring HyperSpectral Data. Discrete Fourier transforms, Lighting, Encoding, Optical interferometry, Spectroscopy, Indexes, Hyperspectral, Compressive sensing BibRef

Hu, J.[Jing], Li, J.X.[Jia-Xin], Wu, X.[Xi], Zhou, J.L.[Ji-Liu],
Noise Robust Single Image Super-Resolution Using a Multiscale Image Pyramid,
ICIP18(2526-2530)
IEEE DOI 1809
Noise measurement, Interpolation, Image resolution, Noise level, Noise robustness, Hafnium, single-image super-resolution, self-similarity BibRef

Kucharczak, F., Mory, C., Strauss, O., Comby, F., Mariano-Goulart, D.,
Regularized selection: A new paradigm for inverse based regularized image reconstruction techniques,
ICIP17(1637-1641)
IEEE DOI 1803
Image reconstruction, Image resolution, Interpolation, Inverse problems, Kernel, Minimization, Regularization, super-resolution BibRef

Xu, J.C.[Jin-Chang], Zhao, Y.[Yu], Dong, Y.[Yuan], Bai, H.L.[Hong-Liang],
Fast and Accurate Image Super-Resolution Using a Combined Loss,
NTIRE17(1093-1099)
IEEE DOI 1709
Convolution, Image reconstruction, Image resolution, Interpolation, Optimization, Testing, Training BibRef

Huang, J.J., Liu, T., Dragotti, P.L., Stathaki, T.,
SRHRF+: Self-Example Enhanced Single Image Super-Resolution Using Hierarchical Random Forests,
NTIRE17(1067-1075)
IEEE DOI 1709
Bagging, Decision trees, Estimation error, Image resolution, Signal resolution, Training, Training, data BibRef

Shoeiby, M.[Mehrdad], Robles-Kelly, A.[Antonio], Wei, R.[Ran], Timofte, R.[Radu],
PIRM2018 Challenge on Spectral Image Super-Resolution: Dataset and Study,
PerceptualRest18(V:276-287).
Springer DOI 1905
BibRef

Ignatov, A.[Andrey], Timofte, R.[Radu], Vu, T.V.[Thang Van], Luu, T.M.[Tung Minh], Pham, T.X.[Trung X.], Nguyen, C.V.[Cao Van], Kim, Y.[Yongwoo], Choi, J.S.[Jae-Seok], Kim, M.C.[Mun-Churl], Huang, J.[Jie], Ran, J.[Jiewen], Xing, C.[Chen], Zhou, X.[Xingguang], Zhu, P.F.[Peng-Fei], Geng, M.[Mingrui], Li, Y.[Yawei], Agustsson, E.[Eirikur], Gu, S.[Shuhang], Van Gool, L.J.[Luc J.], de Stoutz, E.[Etienne], Kobyshev, N.[Nikolay], Nie, K.[Kehui], Zhao, Y.[Yan], Li, G.[Gen], Tong, T.[Tong], Gao, Q.[Qinquan], Hanwen, L.[Liu], Michelini, P.N.[Pablo Navarrete], Dan, Z.[Zhu], Fengshuo, H.[Hu], Hui, Z.[Zheng], Wang, X.[Xiumei], Deng, L.[Lirui], Meng, R.[Rang], Qin, J.[Jinghui], Shi, Y.[Yukai], Wen, W.[Wushao], Lin, L.[Liang], Feng, R.[Ruicheng], Wu, S.[Shixiang], Dong, C.[Chao], Qiao, Y.[Yu], Vasu, S.[Subeesh], Madam, N.T.[Nimisha Thekke], Kandula, P.[Praveen], Rajagopalan, A.N., Liu, J.[Jie], Jung, C.[Cheolkon],
PIRM Challenge on Perceptual Image Enhancement on Smartphones: Report,
PerceptualRest18(V:315-333).
Springer DOI 1905
BibRef

Blau, Y.[Yochai], Mechrez, R.[Roey], Timofte, R.[Radu], Michaeli, T.[Tomer], Zelnik-Manor, L.[Lihi],
The 2018 PIRM Challenge on Perceptual Image Super-Resolution,
PerceptualRest18(V:334-355).
Springer DOI 1905
BibRef

Shoeiby, M.[Mehrdad], Robles-Kelly, A.[Antonio], Timofte, R.[Radu], Zhou, R.[Ruofan], Lahoud, F.[Fayez], Süsstrunk, S.[Sabine], Xiong, Z.W.[Zhi-Wei], Shi, Z.[Zhan], Chen, C.[Chang], Liu, D.[Dong], Zha, Z.J.[Zheng-Jun], Wu, F.[Feng], Wei, K.[Kaixuan], Zhang, T.[Tao], Wang, L.Z.[Li-Zhi], Fu, Y.[Ying], Nagasubramanian, K.[Koushik], Singh, A.K.[Asheesh K.], Singh, A.[Arti], Sarkar, S.[Soumik], Ganapathysubramanian, B.[Baskar],
PIRM2018 Challenge on Spectral Image Super-Resolution: Methods and Results,
PerceptualRest18(V:356-371).
Springer DOI 1905
BibRef

Timofte, R.[Radu], Agustsson, E.[Eirikur], Van Gool, L.J.[Luc J.], Yang, M.H.[Ming-Hsuan], Zhang, L.[Lei], Lim, B.[Bee], Son, S.H.[Sang-Hyun], Kim, H.[Heewon], Nah, S.J.[Seung-Jun], Lee, K.M.[Kyoung Mu], Wang, X.T.[Xin-Tao], Tian, Y.P.[Ya-Peng], Yu, K.[Ke], Zhang, Y.L.[Yu-Lun], Wu, S.X.[Shi-Xiang], Dong, C.[Chao], Lin, L.[Liang], Qiao, Y.[Yu], Loy, C.C.[Chen Change], Bae, W.[Woong], Yoo, J.[Jae_Jun], Han, Y.[Yoseob], Ye, J.C.[Jong Chul], Choi, J.S.[Jae-Seok], Kim, M.C.[Mun-Churl], Fan, Y.C.[Yu-Chen], Yu, J.H.[Jia-Hui], Han, W.[Wei], Liu, D.[Ding], Yu, H.C.[Hai-Chao], Wang, Z.Y.[Zhang-Yang], Shi, H.H.[Hong-Hui], Wang, X.C.[Xin-Chao], Huang, T.S.[Thomas S.], Chen, Y.J.[Yun-Jin], Zhang, K.[Kai], Zuo, W.M.[Wang-Meng], Tang, Z.M.[Zhi-Min], Luo, L.K.[Lin-Kai], Li, S.H.[Shao-Hui], Fu, M.[Min], Cao, L.[Lei], Heng, W.[Wen], Bui, G.[Giang], Le, T.[Truc], Duan, Y.[Ye], Tao, D.C.[Da-Cheng], Wang, R.X.[Ru-Xin], Lin, X.[Xu], Pang, J.X.[Jian-Xin], Xu, J.C.[Jin-Chang], Zhao, Y.[Yu], Xu, X.Y.[Xiang-Yu], Pan, J.S.[Jin-Shan], Sun, D.Q.[De-Qing], Zhang, Y.J.[Yu-Jin], Song, X.B.[Xi-Bin], Dai, Y.C.[Yu-Chao], Qin, X.Y.[Xue-Ying], Huynh, X.P.[Xuan-Phung], Guo, T.T.[Tian-Tong], Mousavi, H.S.[Hojjat Seyed], Vu, T.H.[Tiep Huu], Monga, V.[Vishal], Cruz, C.[Cristovao], Egiazarian, K.[Karen], Katkovnik, V.[Vladimir], Mehta, R.[Rakesh], Jain, A.K.[Arnav Kumar], Agarwalla, A.[Abhinav], Praveen, C.V.S.[C.V. Sai], Zhou, R.F.[Ruo-Fan], Wen, H.D.[Hong-Diao], Zhu, C.[Che], Xia, Z.Q.[Zhi-Qiang], Wang, Z.T.[Zheng-Tao], Guo, Q.[Qi],
NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results,
NTIRE17(1110-1121)
IEEE DOI 1709
Image resolution, Image restoration, MATLAB, Runtime, Testing, Tracking, Training See also NTIRE 2018 Challenge on Image Dehazing: Methods and Results. BibRef

Timofte, R., Gu, S., Van Gool, L.J., Zhang, L., Yang, M.,
NTIRE 2018 Challenge on Single Image Super-Resolution: Methods and Results,
Restoration18(965-96511)
IEEE DOI 1812
Image resolution, Degradation, Training, Runtime, Computer architecture, Testing, Tracking BibRef

Agustsson, E.[Eirikur], Timofte, R.[Radu],
NTIRE 2017 Challenge on Single Image Super-Resolution: Dataset and Study,
NTIRE17(1122-1131)
IEEE DOI 1709
Agriculture, Atmospheric measurements, Degradation, Image quality, Image resolution, Image restoration, Particle, measurements BibRef

You, X.G.[Xin-Ge], Xue, W.Y.[Wei-Yong], Lei, J.J.[Jia-Jia], Zhang, P.[Peng], Cheung, Y.M.[Yiu-Ming], Tang, Y.Y.[Yuan-Yan], Zhou, N.D.[Nai-Ding],
Single image super-resolution with non-local balanced low-rank matrix restoration,
ICPR16(1255-1260)
IEEE DOI 1705
BibRef

Bajic, B.[Buda], Lindblad, J.[Joakim], Sladoje, N.[Nataša],
Single image super-resolution reconstruction in presence of mixed Poisson-Gaussian noise,
IPTA16(1-6)
IEEE DOI 1703
Gaussian distribution BibRef

Mahanti, P., Robinson, M.S., Sato, H., Awumah, A., Henriksen, M.,
Enhancement Of Spatial Resolution of the LROC Wide Angle Camera Images,
ISPRS16(B7: 685-692).
DOI Link 1610
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Choudhury, A., van Beek, P.,
Boosting performance and speed of single-image super-resolution based on partitioned linear regression,
ICIP16(1419-1423)
IEEE DOI 1610
Dictionaries BibRef

Zhou, J., Wu, Y.,
Finding the right exemplars for reconstructing single image super-resolution,
ICIP16(1414-1418)
IEEE DOI 1610
Databases BibRef

Ning, L.[Liu], Shuang, L.[Liang],
Single Image Super-Resolution Using Sparse Representation on a K-NN Dictionary,
ICISP16(169-178).
WWW Link. 1606
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Riegler, G., Schulter, S., Rother, M., Bischof, H.,
Conditioned Regression Models for Non-blind Single Image Super-Resolution,
ICCV15(522-530)
IEEE DOI 1602
Adaptation models BibRef

Kwon, H.[Hyeok_Hyen], Tai, Y.W.[Yu-Wing],
RGB-Guided Hyperspectral Image Upsampling,
ICCV15(307-315)
IEEE DOI 1602
Dictionaries BibRef

Lin, J.H.[Jung-Hsuan], Wang, R.S.[Rong-Sheng], Wang, J.W.[Jing-Wei],
Patch Selection for Single Image Deblurring Based on a Coalitional Game,
ISVC15(II: 521-531).
Springer DOI 1601
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Wei, X.Y.[Xiao-Yao], Dragotti, P.L.[Pier Luigi],
Sampling piecewise smooth signals and its application to image up-sampling,
ICIP15(4293-4297)
IEEE DOI 1512
BibRef

Bai, J.[Jun], Shi, L.M.[Li-Min], Li, B.Y.[Bang-Yu], Xiang, S.M.[Shi-Ming], Pan, C.H.[Chun-Hong],
Super-resolution reconstruction using graph Laplacian penalization,
ICIP15(487-491)
IEEE DOI 1512
Super-resolution reconstruction BibRef

Yu, L.[Lejun], Wu, X.[Xiaoyu], Ge, F.X.[Feng-Xiang], Sun, B.[Bo], He, J.[Jun], Sablatnig, R.[Robert],
Regularized single-image super-resolution based on progressive gradient estimation,
ICIP15(1985-1989)
IEEE DOI 1512
Gradient domain optimization BibRef

Batz, M.[Michel], Eichenseer, A.[Andrea], Seiler, J.[Jurgen], Jonscher, M.[Markus], Kaup, A.[Andre],
Hybrid super-resolution combining example-based single-image and interpolation-based multi-image reconstruction approaches,
ICIP15(58-62)
IEEE DOI 1512
Image Processing BibRef

Zhou, Y.[Yu], Kwong, S.[Sam], Gao, W.[Wei], Zhang, X.[Xiao], Wang, X.[Xu],
Complexity reduction in multi-dictionary based single-image superresolution reconstruction via phase congruency,
ICWAPR15(146-151)
IEEE DOI 1511
computational complexity BibRef

Huang, J.B.[Jia-Bin], Singh, A.[Abhishek], Ahuja, N.[Narendra],
Single image super-resolution from transformed self-exemplars,
CVPR15(5197-5206)
IEEE DOI 1510
Code, Super Resolution.
WWW Link. See also Set5, Set14, Urban 100, BSD 100, Sun-Hays 80 Datasets. BibRef

Set5, Set14, Urban 100, BSD 100, Sun-Hays 80 Datasets,
Dataset, Super Resolution. Linkd from:
WWW Link.

Ferreira, J.C., Le Meur, O., Guillemot, C., da Silva, E.A.B., Carrijo, G.A.,
Single image super-resolution using sparse representations with structure constraints,
ICIP14(3862-3866)
IEEE DOI 1502
Dictionaries BibRef

Zhu, Y.[Yu], Zhang, Y.N.[Yan-Ning], Bonev, B.[Boyan], Yuille, A.L.[Alan L.],
Modeling deformable gradient compositions for single-image super-resolution,
CVPR15(5417-5425)
IEEE DOI 1510
BibRef

Zhu, Y.[Yu], Zhang, Y.N.[Yan-Ning], Yuille, A.L.[Alan L.],
Single Image Super-resolution Using Deformable Patches,
CVPR14(2917-2924)
IEEE DOI 1409
deformable patches;single super-resolution BibRef

Yang, C.Y.[Chih-Yuan], Ma, C.[Chao], Yang, M.H.[Ming-Hsuan],
Single-Image Super-Resolution: A Benchmark,
ECCV14(IV: 372-386).
Springer DOI 1408
BibRef

Deka, B., Gorain, K.K., Kalita, N., Das, B.,
Single image super-resolution using compressive sensing with learned overcomplete dictionary,
NCVPRIPG13(1-5)
IEEE DOI 1408
compressed sensing BibRef

Lin, W.T.[Wun-Ting], Lai, S.H.[Shang-Hong],
Single Image Super-Resolution Based on Local Self-Similarity,
ACPR13(191-195)
IEEE DOI 1408
computer vision BibRef

Ram, S., Rodriguez, J.J.,
Image super-resolution using graph regularized block sparse representation,
Southwest16(69-72)
IEEE DOI 1605
BibRef
Earlier:
Single image super-resolution using dictionary-based local regression,
Southwest14(121-124)
IEEE DOI 1406
Image resolution. approximation theory BibRef

Yu, L.C.[Li-Cheng], Xu, Y.[Yi], Zhang, B.[Bo],
Single image super-resolution via phase congruency analysis,
VCIP13(1-6)
IEEE DOI 1402
fractals BibRef

Timofte, R.[Radu], de Smet, V.[Vincent], Van Gool, L.J.[Luc J.],
A+: Adjusted Anchored Neighborhood Regression for Fast Super-Resolution,
ACCV14(IV: 111-126).
Springer DOI 1504
BibRef
Earlier:
Anchored Neighborhood Regression for Fast Example-Based Super-Resolution,
ICCV13(1920-1927)
IEEE DOI 1403
anchored neighborhood regression BibRef

Efrat, N.[Netalee], Glasner, D.[Daniel], Apartsin, A.[Alexander], Nadler, B.[Boaz], Levin, A.[Anat],
Accurate Blur Models vs. Image Priors in Single Image Super-resolution,
ICCV13(2832-2839)
IEEE DOI 1403
BibRef

Salvador, J.[Jordi], Perez-Pellitero, E.[Eduardo], Kochale, A.[Axel],
Robust single-image super-resolution using cross-scale self-similarity,
ICIP14(2135-2139)
IEEE DOI 1502
BibRef
Earlier:
Fast single-image super-resolution with filter selection,
ICIP13(640-644)
IEEE DOI 1402
Image resolution. Bandwidth BibRef

Turkan, M.[Mehmet], Thoreau, D.[Dominique], Guillotel, P.[Philippe],
Iterated neighbor-embeddings for image super-resolution,
ICIP14(3887-3891)
IEEE DOI 1502
BibRef
Earlier:
Optimized neighbor embeddings for single-image super-resolution,
ICIP13(645-649)
IEEE DOI 1402
Estimation. Geometry BibRef

Zhong, L.[Lin], Cho, S.H.[Sung-Hyun], Metaxas, D.N.[Dimitris N.], Paris, S.[Sylvain], Wang, J.[Jue],
Handling Noise in Single Image Deblurring Using Directional Filters,
CVPR13(612-619)
IEEE DOI 1309
BibRef

Harmeling, S.[Stefan], Hirsch, M.[Michael], Scholkopf, B.[Bernhard],
On a Link Between Kernel Mean Maps and Fraunhofer Diffraction, with an Application to Super-Resolution Beyond the Diffraction Limit,
CVPR13(1083-1090)
IEEE DOI 1309
BibRef

Han, Y.S.[Yun-Sang], Chae, T.B.[Tae Byeong], Lee, S.K.[Sang-Keun],
Non-parametric single image super resolution,
FCV13(281-284).
IEEE DOI 1304
BibRef

Shibata, T.[Takashi], Iketani, A.[Akihiko], Senda, S.[Shuji],
Single Image Super Resolution Reconstruction in Perturbed Exemplar Sub-space,
ACCV12(III:401-412).
Springer DOI 1304
BibRef

Trinh, D.H.[Dinh Hoan], Luong, M., Rocchisani, J., Pham, C.D.[Canh Duong], Pham, H.D.[Huy Dien], Dibos, F.,
An Optimal Weight Model for Single Image Super-Resolution,
DICTA12(1-8).
IEEE DOI 1303
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Lee, J.[Jongho], Ahn, S.C.[Sang Chul], Lim, H.[Hwasup], Kim, I.J.[Ig-Jae], Kim, J.W.[Jae-Won], Kim, H.G.[Hyoung-Gon],
Web image-based super-resolution,
ICPR12(1060-1063).
WWW Link. 1302
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He, H.Y.[Hua-Yong], Li, J.H.[Jian-Hong], Luo, X.N.[Xiao-Nan],
Single Image Super-Resolution Using Gaussian Mixture Model,
ICPR12(1916-1919).
WWW Link. 1302
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Patel, R.C., Joshi, M.V.,
Super-resolution of Hyperspectral Images Using Compressive Sensing Based Approach,
AnnalsPRS(I-7), No. 2012, pp. 83-88.
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Islam, M.M.[Mohammad M.], Asari, V.K.[Vijayan K.], Islam, M.N.[Mohammed N.], Karim, M.A.[Mohammad A.],
Single image super-resolution in frequency domain,
Southwest12(53-56).
IEEE DOI 1205
BibRef

Liao, R.J.[Ren-Jie], Qin, Z.C.[Zeng-Chang],
Image Super-Resolution Using Local Learnable Kernel Regression,
ACCV12(III:349-360).
Springer DOI 1304
BibRef

Zhang, Y.N.[Yan-Ning], Zhang, H.C.[Hai-Chao], Huang, T.S.[Thomas S.],
Collaborative and compressive high-resolution imaging,
ICPR12(3062-3065).
WWW Link. 1302
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Taniguchi, K.[Kazuki], Han, X.H.[Xian-Hua], Iwamoto, Y.[Yutaro], Sasatani, S.[So], Chen, Y.W.[Yen-Wei],
Image super-resolution based on locality-constrained linear coding,
ICPR12(1948-1951).
WWW Link. 1302
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Gu, Y.[Ying], Qu, Y.[Yanyun], Fang, T.Z.[Tian-Zhu], Li, C.[Cuihua], Wang, H.Z.[Han-Zi],
Image super-resolution based on multikernel regression,
ICPR12(2071-2074).
WWW Link. 1302
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Zhu, Y.M.[Yan-Ming], Jiang, J.M.[Jian-Min], Li, K.[Kun],
Optimized image super-resolution based on sparse representation,
ICPR12(1052-1055).
WWW Link. 1302
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Lin, C.Y.[Chun-Yu], Hsu, C.C.[Chih-Chung], Lin, C.W.[Chia-Wen], Kang, L.W.[Li-Wei],
Fast deconvolution-based image super-resolution using gradient prior,
VCIP11(1-4).
IEEE DOI 1201
BibRef

He, H.[He], Siu, W.C.[Wan-Chi],
Single Image Super-Resolution Using Gaussian Process Regression,
CVPR11(449-456).
IEEE DOI 1106
BibRef

Huang, K.[Kebin], Hu, R.M.[Rui-Min], Han, Z.[Zhen], Wang, F.[Feng],
A super-resolution method based on local sparse and global gradient,
IASP11(261-265).
IEEE DOI 1112
BibRef

Ravishankar, S.[Subrahmanyam], Reddy, C.N.[Challapalle Nagadastagiri], Tripathi, S.[Shikha], Murthy, K.V.V.,
Image Super Resolution Using Sparse Image and Singular Values as Priors,
CAIP11(II: 380-388).
Springer DOI 1109
BibRef

Watanabe, H.[Hiroki], Yamamoto, A.[Akifumi], Fujiwara, T.[Takayuki], Funahashi, T.[Takuma], Koshimizu, H.[Hiroyasu],
Super-resolution in gray value based on OK quantization theory,
FCV11(1-6).
IEEE DOI 1102
BibRef

Song, H.H.[Hui-Hui], Zhang, L.[Lei], Wang, P.K.[Pei-Kang], Zhang, K.H.[Kai-Hua], Li, X.[Xin],
AN adaptive L1-L2 hybrid error model to super-resolution,
ICIP10(2821-2824).
IEEE DOI 1009
BibRef

Yan, R.M.[Ruo-Mei], Zhang, Y.F.[Yun-Feng], Li, Y.S.[Yun-Song], Wu, C.K.[Cheng-Ke],
Super-resolution image reconstruction based on guided cost function,
ICIP10(1985-1988).
IEEE DOI 1009
BibRef

Fu, Z.Z.[Zhi-Zhong], Li, Z.N.[Ze-Ning], Ding, L.[Lan], Nguyen, T.[Truong],
Translation invariance-based super resolution method for mixed resolution multiview video,
ICIP14(5457-5461)
IEEE DOI 1502
Estimation BibRef

Liu, Q.[Qing], Wang, S.A.[Sun-An], Zhang, X.H.[Xiao-Hui], Hou, Y.[Yun],
Improvement of the space resolution of the optical remote sensing image by the principle of CCD imaging,
IPTA10(477-481).
IEEE DOI 1007
BibRef

Li, B.[Bo], Chang, H.[Hong], Shan, S.G.[Shi-Guang], Chen, X.L.[Xi-Lin],
Locality preserving constraints for super-resolution with neighbor embedding,
ICIP09(1189-1192).
IEEE DOI 0911
BibRef

Glasner, D.[Daniel], Bagon, S.[Shai], Irani, M.[Michal],
Super-resolution from a single image,
ICCV09(349-356).
IEEE DOI 0909
BibRef

Ružic, T.[Tijana], Luong, H.Q.[Hięp Q.], Pižurica, A.[Aleksandra], Philips, W.[Wilfried],
Single Image Example-Based Super-Resolution Using Cross-Scale Patch Matching and Markov Random Field Modelling,
ICIAR11(I: 11-20).
Springer DOI 1106
BibRef

Yang, C.Y.[Chih-Yuan], Yang, M.H.[Ming-Hsuan],
Fast Direct Super-Resolution by Simple Functions,
ICCV13(561-568)
IEEE DOI 1403
cluster; fast; linear regression; single-image super-resolution; subspace BibRef

Yang, C.Y.[Chih-Yuan], Huang, J.B.[Jia-Bin], Yang, M.H.[Ming-Hsuan],
Exploiting Self-similarities for Single Frame Super-Resolution,
ACCV10(III: 497-510).
Springer DOI 1011
BibRef

Xu, X.Y.[Xin-Yu], Pan, H.[Hao],
Finding the splitting vector for image resolution up-conversion,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Martins, A.L.D.[Ana L.D.], Levada, A.L.M.[Alexandre L.M.], Homem, M.R.P.[Murillo R.P.], Mascarenhas, N.D.A.[Nelson D.A.],
Map-MRF Super-Resolution Image Reconstruction using Maximum Pseudo-Likelihood parameter estimation,
ICIP09(1165-1168).
IEEE DOI 0911
BibRef

Martins, A.L.D., Homem, M.R.P., Mascarenhas, N.D.A.,
Super-Resolution Image Reconstruction using the ICM Algorithm,
ICIP07(IV: 205-208).
IEEE DOI 0709
BibRef

Yan, P.M.[Pei-Min], Wang, S.Z.[Shuo-Zhong],
Iterative Image Resolution Enhancement Using MAP Estimator,
ICARCV06(1-3).
IEEE DOI 0612
BibRef

Katartzis, A.[Antonis], Petrou, M.[Maria],
Robust Bayesian Estimation and Normalized Convolution for Super-resolution Image Reconstruction,
Fusion07(1-7).
IEEE DOI 0706
BibRef

Zhao, S.[Shubin],
Multi-scale MAP Estimation of High-Resolution Images,
PSIVT06(1059-1066).
Springer DOI 0612
BibRef

Chang, T.L.[Tien-Lung], Liu, T.L.[Tyng-Luh], Chuang, J.H.[Jen-Hui],
Direct Energy Minimization for Super-Resolution on Nonlinear Manifolds,
ECCV06(IV: 281-294).
Springer DOI 0608
See also probabilistic SVM approach for background scene initialization, A. BibRef

Prendergast, R.S., Nguyen, T.Q.,
Improving Frequency Domain Super-Resolution via Undersampling Model,
ICIP05(I: 853-856).
IEEE DOI 0512
BibRef

Wang, Q.A.[Qi-Ang], Tang, X.O.[Xiao-Ou], Shum, H.Y.[Heung-Yeung],
Patch Based Blind Image Super Resolution,
ICCV05(I: 709-716).
IEEE DOI 0510
BibRef

Czúni, L.[László], Császár, G.[Gergely], Cho, D.S.[Dae-Sung], Kim, H.M.[Hyun Mun],
New Algorithms for Example-Based Super-Resolution,
CAIP05(781).
Springer DOI 0509
BibRef

Czúni, L.[László], Csordás, D.[Dezso], Császár, G.[Gergely],
Distance Map Retrieval,
ICIAR04(I: 811-817).
Springer DOI 0409
BibRef

Chang, H.[Hong], Yeung, D.Y.[Dit-Yan], Xiong, Y.M.[Yi-Min],
Super-resolution through neighbor embedding,
CVPR04(I: 275-282).
IEEE DOI 0408
BibRef

Shapiro, V.[Vladimir],
Super-resolution Capabilities of the Hough-Green Transform,
CAIP03(673-680).
Springer DOI 0311
BibRef

Lan, T.[Tsehua], Chen, Y.W.[Ying-Wei], van Zon, K.[Kees],
Complexity-Scalable Algorithmic Design: Implementation of a Scalable Resolution Enhancement Algorithm,
ICIP02(II: 877-880).
IEEE DOI 0210
BibRef

Ponik, T.[Tomas], Placek, J.[Jaroslav],
The Resolution Enhancement by Software Method of Random Shift,
PCV02(A: 258). 0305
BibRef

Kursun, O., Favorov, O.,
Single-frame super-resolution by a cortex based mechanism using high level visual features in natural images,
WACV02(112-117).
IEEE DOI 0303
BibRef

Ferreira, P.J.S.G.,
Two fast extrapolation/superresolution algorithms,
ICIP00(Vol II: 343-346).
IEEE DOI 0403
BibRef

Bhattacharjee, S., Sundareshan, M.,
Modeling and Extrapolation of Prior Scene Information for Set Theoretic Restoration and Super-resolution of Diffraction-limited Images,
ICIP00(Vol II: 347-350).
IEEE DOI 0008
BibRef

van Vliet, L.J., Hendriks, C.L.L.,
Improving Spatial Resolution in Exchange of Temporal Resolution in Aliased Image Sequences,
SCIA99(Industrial Applications). BibRef 9900

Calle, D., Montanvert, A.,
Super-resolution inducing of an image,
ICIP98(III: 232-236).
IEEE DOI 9810
BibRef

Papageorgiou, C.[Constantine], Girosi, F.[Fredrico], Poggio, T.[Tomaso],
Correlation Kernel Reconstruction and Superresolution,
DARPA98(1025-1030). BibRef 9800

Connolly, T.J., Lane, R.G.,
Constrained regularization methods for superresolution,
ICIP98(III: 727-731).
IEEE DOI 9810
BibRef
Earlier:
Gradient Methods for Superresolution,
ICIP97(I: 917-920).
IEEE DOI BibRef

Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Learning, Neural Nets for Single Image Super Resolution .


Last update:Dec 7, 2019 at 17:16:29