Koike, K.[Kazumasa],
Image processor which converts image with poor resolution
into image with improved resolution,
US_Patent5,231,519, Jul 27, 1993
WWW Link.
BibRef
9307
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
WWW Link.
BibRef
0107
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
BibRef
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,
VISP(147), No. 4, 2000, pp. 318-322.
0010
BibRef
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
Nagahara, H.[Hajime],
Liu, D.Y.[Deng-Yu],
Sonoda, T.[Toshiki],
Gu, J.W.[Jin-Wei],
Space-Time-Brightness Sampling Using an Adaptive Pixel-Wise Coded
Exposure,
CCD18(1915-19158)
IEEE DOI
1812
Spatial resolution, Cameras, Brightness, Image reconstruction, Dynamic range
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
Mei, Y.Q.[Yi-Qun],
Fan, Y.C.[Yu-Chen],
Zhou, Y.Q.[Yu-Qian],
Image Super-Resolution with Non-Local Sparse Attention,
CVPR21(3516-3525)
IEEE DOI
2111
Computational modeling, Superresolution,
Computer architecture, Benchmark testing, Robustness, Pattern recognition
BibRef
Mei, Y.Q.[Yi-Qun],
Fan, Y.C.[Yu-Chen],
Zhou, Y.Q.[Yu-Qian],
Huang, L.C.[Li-Chao],
Huang, T.S.[Thomas S.],
Shi, H.H.[Hong-Hui],
Image Super-Resolution With Cross-Scale Non-Local Attention and
Exhaustive Self-Exemplars Mining,
CVPR20(5689-5698)
IEEE DOI
2008
Correlation, Feature extraction, Computer architecture,
Image reconstruction, Microprocessors, Spatial resolution
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
do Nascimento, T.P.,
Salles, E.O.T.[Evandro O. Teatini],
Multi-Frame Super-Resolution Combining Demons Registration and
Regularized Bayesian Reconstruction,
SPLetters(27), 2020, pp. 2009-2013.
IEEE DOI
2012
Image reconstruction, Signal processing algorithms,
Bayes methods, Mathematical model, AWGN,
Bayesian super-resolution
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.X.[Ya-Xin],
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.X.[Ya-Xin],
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
Zhang, Y.Q.[Yong-Qin],
Liu, J.Y.[Jia-Ying],
Yang, W.,
Guo, Z.M.[Zong-Ming],
Image Super-Resolution Based on Structure-Modulated Sparse
Representation,
IP(24), No. 9, September 2015, pp. 2797-2810.
IEEE DOI
1506
Dictionaries
BibRef
Zhang, Y.Q.[Yong-Qin],
Liu, J.Y.[Jia-Ying],
Bai, W.[Wei],
Guo, Z.M.[Zong-Ming],
Exploiting multi-scale spatial structures for sparsity based single
image super-resolution,
ICIP14(3877-3881)
IEEE DOI
1502
Dictionaries
BibRef
Ren, J.[Jie],
Liu, J.Y.[Jia-Ying],
Guo, Z.M.[Zong-Ming],
Context-Aware Sparse Decomposition for Image Denoising and
Super-Resolution,
IP(22), No. 4, April 2013, pp. 1456-1469.
IEEE DOI
1303
BibRef
Bai, W.[Wei],
Yang, S.,
Liu, J.Y.[Jia-Ying],
Ren, J.[Jie],
Guo, Z.M.[Zong-Ming],
Image super resolution using saliency-modulated context-aware sparse
decomposition,
VCIP13(1-6)
IEEE DOI
1402
compressed sensing
BibRef
Ren, J.[Jie],
Liu, J.Y.[Jia-Ying],
Wang, M.Y.[Meng-Yan],
Guo, Z.M.[Zong-Ming],
Image super-resolution by structural sparse coding,
ICPR12(1936-1939).
WWW Link.
1302
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
Timofte, R.[Radu],
de Smet, V.[Vincent],
Van Gool, L.J.[Luc J.],
Semantic super-resolution: When and where is it useful?,
CVIU(142), No. 1, 2016, pp. 1-12.
Elsevier DOI
1512
Single-image super-resolution
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.[Xin],
Liu, Q.[Qian],
Li, X.M.[Xue-Mei],
Zhou, Y.F.[Yuan-Feng],
Zhang, C.M.[Cai-Ming],
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
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
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.
WWW Link.
1708
BibRef
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
BibRef
Gong, W.G.[Wei-Guo],
Yi, Q.[Qiane],
Tang, Y.L.[Yong-Liang],
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
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.Z.[Zeng-Zeng],
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
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.[Qiang],
Zhang, P.[Peng],
Bao, F.X.[Fang-Xun],
Weighted Adaptive Image Super-Resolution Scheme Based on Local
Fractal Feature and Image Roughness,
MultMed(23), 2021, pp. 1426-1441.
IEEE DOI
2105
Fractals, Image resolution, Image edge detection, Interpolation,
Image segmentation, Rough surfaces, Surface roughness,
sub-block selection
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.Z.[Qi-Zhi],
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
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
BibRef
Tao, Y.[Yu],
Muller, J.P.[Jan-Peter],
Super-Resolution Restoration of Spaceborne Ultra-High-Resolution
Images Using the UCL OpTiGAN System,
RS(13), No. 12, 2021, pp. xx-yy.
DOI Link
2106
BibRef
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
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
BibRef
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.J.[Shu-Jin],
Li, Y.H.[Yue-Hua],
Single Image Super-Resolution under Multi-Frame Method,
SIViP(13), No. 2, March 2019, pp. 331-339.
WWW Link.
1904
BibRef
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
BibRef
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.F.[Yu-Feng],
Fast HSI super resolution using linear regression,
IET-IPR(13), No. 10, 22 August 2019, pp. 1671-1679.
DOI Link
1909
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
Wang, R.,
Gong, M.,
Tao, D.,
Receptive Field Size Versus Model Depth for Single Image
Super-Resolution,
IP(29), No. 1, 2020, pp. 1669-1682.
IEEE DOI
1912
Convolution, Image resolution, Computer architecture,
Task analysis, Interpolation, Computational modeling,
single image super-resolution
BibRef
Yang, W.M.[Wen-Ming],
Zhang, X.C.[Xue-Chen],
Tian, Y.P.[Ya-Peng],
Wang, W.[Wei],
Xue, J.H.[Jing-Hao],
Liao, Q.M.[Qing-Min],
Deep Learning for Single Image Super-Resolution: A Brief Review,
MultMed(21), No. 12, December 2019, pp. 3106-3121.
IEEE DOI
1912
Image resolution, Convolution, Deep learning,
Machine learning algorithms, Computer architecture,
objective function
BibRef
Suryanarayana, G.[Gunnam],
Dhuli, R.[Ravindra],
Yang, J.[Jie],
Single Image Super-Resolution Algorithm Possessing Edge and Contrast
Preservation,
IJIG(19), No. 4 2019, pp. 1950024.
DOI Link
2001
BibRef
Li, X.S.[Xue-Song],
Cao, G.[Guo],
Zhang, Y.Q.[You-Qiang],
Shafique, A.[Ayesha],
Fu, P.[Peng],
Combining synthesis sparse with analysis sparse for single image
super-resolution,
SP:IC(83), 2020, pp. 115805.
Elsevier DOI
2003
Analysis sparse coding, Global and nonlocal optimization,
Soft threshold shrinkage, Super-resolution, Synthesis sparse coding
BibRef
Kim, H.,
Kim, G.,
Single Image Super-Resolution Using Fire Modules With Asymmetric
Configuration,
SPLetters(27), 2020, pp. 516-519.
IEEE DOI
2005
Convolution, Feature extraction, Image reconstruction,
Spatial resolution, Deep learning,
asymmetric configuration of fire modules
BibRef
Pandey, G.[Garima],
Ghanekar, U.[Umesh],
Classification of priors and regularization techniques appurtenant to
single image super-resolution,
VC(36), No. 6, June 2020, pp. 1291-1304.
Springer DOI
2005
BibRef
Dehkordi, R.A.[Rasoul Asgarian],
Khosravi, H.[Hossein],
Ahmadyfard, A.[Alireza],
Single image super-resolution based on sparse representation using
dictionaries trained with input image patches,
IET-IPR(14), No. 8, 19 June 2020, pp. 1587-1593.
DOI Link
2005
BibRef
Zhang, Y.,
Wang, P.,
Bao, F.,
Yao, X.,
Zhang, C.,
Lin, H.,
A Single-Image Super-Resolution Method Based on Progressive-Iterative
Approximation,
MultMed(22), No. 6, June 2020, pp. 1407-1422.
IEEE DOI
2005
Image edge detection, Interpolation, Surface reconstruction,
Image reconstruction, Splines (mathematics), Surface topography,
curve geometric iteration
BibRef
Bai, Y.C.[Yuan-Chao],
Jia, H.Z.[Hui-Zhu],
Jiang, M.[Ming],
Liu, X.M.[Xian-Ming],
Xie, X.D.[Xiao-Dong],
Gao, W.[Wen],
Single-Image Blind Deblurring Using Multi-Scale Latent Structure
Prior,
CirSysVideo(30), No. 7, July 2020, pp. 2033-2045.
IEEE DOI
2007
Image restoration, Kernel, Optimization, Estimation, Convolution,
Frequency-domain analysis, Image resolution,
uniform and non-uniform deblurring
BibRef
Zhang, J.[Jing],
Shao, M.H.[Min-Hao],
Yu, L.L.[Lu-Lu],
Li, Y.S.[Yun-Song],
Image super-resolution reconstruction based on sparse representation
and deep learning,
SP:IC(87), 2020, pp. 115925.
Elsevier DOI
2007
Sparse representation, Deep learning, Super-resolution, Feature fusion
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
Mikaeli, E.[Elhameh],
Aghagolzadeh, A.[Ali],
Azghani, M.[Masoumeh],
Single-image super-resolution via patch-based and group-based local
smoothness modeling,
VC(36), No. 8, August 2020, pp. 1573-1589.
WWW Link.
2007
BibRef
Li, K.[Kai],
Yang, S.H.[Sheng-Hao],
Dong, R.T.[Run-Ting],
Wang, X.Y.[Xiao-Ying],
Huang, J.Q.A.[Jian-Qi-Ang],
Survey of single image super-resolution reconstruction,
IET-IPR(14), No. 11, September 2020, pp. 2273-2290.
DOI Link
2009
Survey, Super-Resolution.
BibRef
Chantas, G.,
Nikolopoulos, S.N.,
Kompatsiaris, I.[Ioannis],
Heavy-Tailed Self-Similarity Modeling for Single Image Super
Resolution,
IP(30), 2021, pp. 838-852.
IEEE DOI
2012
Image resolution, Probabilistic logic, Indexes, Imaging, Measurement,
Spatial resolution, Mathematical model,
non local means
BibRef
Wang, M.H.[Ming-Hua],
Wang, Q.[Qiang],
Hypergraph-regularized sparse representation for single color image
super resolution,
JVCIR(74), 2021, pp. 102951.
Elsevier DOI
2101
Color image super resolution,
Alternating Direction Method of Multipliers (ADMM),
Self-channel and cross-channel information
BibRef
Liu, Y.N.[Yu-Nan],
Zhang, S.S.[Shan-Shan],
Wang, C.P.[Chun-Peng],
Xu, J.[Jie],
Single image super-resolution via hybrid resolution NSST prediction,
CVIU(207), 2021, pp. 103202.
Elsevier DOI
2105
Convolutional neural networks, Single image super-resolution,
Nonsubsampled shearlet transform, Hybrid resolution network
BibRef
López-Tapia, S.[Santiago],
de la Blanca, N.P.[Nicolás Pérez],
Fast and Robust Cascade Model for Multiple Degradation Single Image
Super-Resolution,
IP(30), 2021, pp. 4747-4759.
IEEE DOI
2105
BibRef
Tao, Y.[Yu],
Conway, S.J.[Susan J.],
Muller, J.P.[Jan-Peter],
Putri, A.R.D.[Alfiah R. D.],
Thomas, N.[Nicolas],
Cremonese, G.[Gabriele],
Single Image Super-Resolution Restoration of TGO CaSSIS Colour
Images: Demonstration with Perseverance Rover Landing Site and Mars
Science Targets,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link
2105
BibRef
Tao, Y.[Yu],
Xiong, S.[Siting],
Song, R.[Rui],
Muller, J.P.[Jan-Peter],
Towards Streamlined Single-Image Super-Resolution: Demonstration with
10 m Sentinel-2 Colour and 10-60 m Multi-Spectral VNIR and SWIR Bands,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link
2107
BibRef
Li, Y.W.[Yao-Wei],
Luo, Y.[Ye],
Zhang, G.K.[Guo-Kai],
Lu, J.W.[Jian-Wei],
Single image deblurring with cross-layer feature fusion and
consecutive attention,
JVCIR(78), 2021, pp. 103149.
Elsevier DOI
2107
Image deblurring, Cross-layer feature fusion, Consecutive attention
BibRef
Vella, M.[Marija],
Mota, J.F.C.[Joăo F. C.],
Robust Single-Image Super-Resolution via CNNs and TV-TV Minimization,
IP(30), 2021, pp. 7830-7841.
IEEE DOI
2109
Image reconstruction, Training, TV, Optimization, Testing,
Minimization, Task analysis, Image super-resolution, prior information
BibRef
Wan, W.X.[Wei-Xiao],
Zhang, B.[Bowen],
Vella, M.[Marija],
Mota, J.F.C.[Joăo F.C.],
Chen, W.[Wei],
Robust RGB-Guided Super-Resolution of Hyperspectral Images via TV^3
Minimization,
SPLetters(29), 2022, pp. 957-961.
IEEE DOI
2205
BibRef
Earlier: A3, A2, A5, A4, Only:
Enhanced Hyperspectral Image Super-Resolution via RGB Fusion and
TV-TV Minimization,
ICIP21(3837-3841)
IEEE DOI
2201
TV, Image color analysis, Training, Superresolution, Cameras, Testing,
Spatial resolution, TV^3 minimization.
Current measurement, Surveillance,
Neural networks, Extraterrestrial measurements, Minimization,
total variation
BibRef
Jiang, W.Z.[Wen-Zong],
Zhao, L.F.[Li-Fei],
Wang, Y.J.[Yan-Jiang],
Liu, W.F.[Wei-Feng],
Liu, B.[Baodi],
Cross-Dimension Attention Guided Self-Supervised Remote Sensing
Single-Image Super-Resolution,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Liu, B.[Baodi],
Zhao, L.F.[Li-Fei],
Li, J.Y.[Jiao-Yue],
Zhao, H.L.[Heng-Le],
Liu, W.F.[Wei-Feng],
Li, Y.[Ye],
Wang, Y.J.[Yan-Jiang],
Chen, H.L.[Hong-Long],
Cao, W.J.[Wei-Jia],
Saliency-Guided Remote Sensing Image Super-Resolution,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Chen, R.[Rui],
Zhang, H.[Heng],
Liu, J.X.[Ji-Xin],
Multi-Attention Augmented Network for Single Image Super-Resolution,
PR(122), 2022, pp. 108349.
Elsevier DOI
2112
Super-resolution, Multi-scale U-net,
pre-defined sparse kernels, Attention mechanism
See also MCHA-Net: A Multi-End Composite Higher-Order Attention Network Guided with Hierarchical Supervised Signal for High-Resolution Remote Sensing Image Change Detection.
BibRef
Chen, R.[Rui],
Zhang, Y.[Yan],
Learning Dynamic Generative Attention for Single Image
Super-Resolution,
CirSysVideo(32), No. 12, December 2022, pp. 8368-8382.
IEEE DOI
2212
Image reconstruction, Superresolution, Visualization,
Feature extraction, Deep learning, Transforms,
multi-scale variational encoder
BibRef
Kang, X.J.[Xue-Jing],
Duan, P.Q.[Pei-Qi],
Xu, R.[Ruyu],
Single image super-resolution based on mapping-vector clustering and
nonlinear pixel-reconstruction,
SP:IC(100), 2022, pp. 116501.
Elsevier DOI
2112
Super resolution, Patch reconstruction, Decision-tree,
Nonlinear-mapping learning
BibRef
Salgueiro, L.[Luis],
Marcello, J.[Javier],
Vilaplana, V.[Verónica],
Single-Image Super-Resolution of Sentinel-2 Low Resolution Bands with
Residual Dense Convolutional Neural Networks,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link
2112
BibRef
Basioti, K.[Kalliopi],
Moustakides, G.V.[George V.],
Single Image Restoration with Generative Priors,
ICIP21(1679-1683)
IEEE DOI
2201
Computational modeling, Superresolution, Probability, Distortion,
Image restoration, Mathematical model, Task analysis,
Generative modeling
BibRef
Du, X.B.[Xiao-Biao],
Jiang, S.B.[Sai-Biao],
Liu, J.[Jie],
Augmented global attention network for image super-resolution,
IET-IPR(16), No. 2, 2022, pp. 567-575.
DOI Link
2201
BibRef
Han, Y.Z.[Yu-Zhuo],
Du, X.B.[Xiao-Biao],
Yang, Z.[Zhi],
Two-Stage Network for Single Image Super-Resolution,
UG21(880-887)
IEEE DOI
2109
Inverse problems,
Computational modeling, Superresolution, Transforms, Pattern recognition
BibRef
Cai, Q.[Qing],
Li, J.X.[Jin-Xing],
Li, H.F.[Hua-Feng],
Yang, Y.H.[Yee-Hong],
Wu, F.[Feng],
Zhang, D.[David],
TDPN: Texture and Detail-Preserving Network for Single Image
Super-Resolution,
IP(31), 2022, pp. 2375-2389.
IEEE DOI
2203
Visualization, Convolutional neural networks, Superresolution,
Generative adversarial networks, Feature extraction, Convolution,
multi-reception field module
BibRef
Jiang, Q.P.[Qiu-Ping],
Liu, Z.T.[Zhen-Tao],
Gu, K.[Ke],
Shao, F.[Feng],
Zhang, X.F.[Xin-Feng],
Liu, H.T.[Han-Tao],
Lin, W.S.[Wei-Si],
Single Image Super-Resolution Quality Assessment:
A Real-World Dataset, Subjective Studies, and an Objective Metric,
IP(31), 2022, pp. 2279-2294.
IEEE DOI
2203
Measurement, Degradation, Cameras, Superresolution,
Quality assessment, Image segmentation,
Karhunen-Loéve transform
BibRef
Guo, P.F.[Peng-Fei],
He, L.[Lang],
Liu, S.Y.[Shuang-Yin],
Zeng, D.[Delu],
Liu, H.T.[Han-Tao],
Underwater Image Quality Assessment: Subjective and Objective Methods,
MultMed(24), No. 2022, pp. 1980-1989.
IEEE DOI
2204
Image enhancement, Measurement, Histograms, Image color analysis,
Image quality, Image restoration, Benchmark testing,
objective metric
BibRef
Zhang, J.Z.[Ji-Zhou],
Xu, T.F.[Ting-Fa],
Li, J.N.[Jia-Nan],
Jiang, S.W.[Shen-Wang],
Zhang, Y.H.[Yu-Han],
Single-Image Super Resolution of Remote Sensing Images with
Real-World Degradation Modeling,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link
2206
BibRef
Niu, A.[Axi],
Zhu, Y.[Yu],
Zhang, C.N.[Chao-Ning],
Sun, J.Q.[Jin-Qiu],
Wang, P.[Pei],
Kweon, I.S.[In So],
Zhang, Y.N.[Yan-Ning],
MS2Net: Multi-Scale and Multi-Stage Feature Fusion for Blurred Image
Super-Resolution,
CirSysVideo(32), No. 8, August 2022, pp. 5137-5150.
IEEE DOI
2208
Superresolution, Image resolution, Fuses, Degradation, Kernel,
Feature extraction, Task analysis, Single image super-resolution,
multi-stage feature fusion
BibRef
He, Z.W.[Ze-Wei],
Chen, D.[Du],
Cao, Y.P.[Yan-Peng],
Yang, J.X.[Jiang-Xin],
Cao, Y.L.[Yan-Long],
Li, X.[Xin],
Tang, S.L.[Si-Liang],
Zhuang, Y.T.[Yue-Ting],
Lu, Z.M.[Zhe-Ming],
Single image super-resolution based on progressive fusion of
orientation-aware features,
PR(133), 2023, pp. 109038.
Elsevier DOI
2210
Single image super-resolution, Channel attention,
Orientation-aware, Feature extraction, Feature fusion
BibRef
Behjati, P.[Parichehr],
Rodriguez, P.[Pau],
Fernández, C.[Carles],
Hupont, I.[Isabelle],
Mehri, A.[Armin],
Gonzŕlez, J.[Jordi],
Single image super-resolution based on directional variance attention
network,
PR(133), 2023, pp. 108997.
Elsevier DOI
2210
Single image super-resolution, Efficient network, Attention mechanism
BibRef
Tang, Y.G.[Ying-Gan],
Liu, C.L.[Cheng-Lu],
Zhang, X.G.[Xu-Guang],
Single image super-resolution using Wasserstein generative
adversarial network with gradient penalty,
PRL(163), 2022, pp. 32-39.
Elsevier DOI
2212
Image, Super-resolution, Generative adversarial network,
Gradient penalty, Residual network
BibRef
Zuo, Y.F.[Yi-Fan],
Xie, J.C.[Jia-Cheng],
Wang, H.[Hao],
Fang, Y.M.[Yu-Ming],
Liu, D.[Deyang],
Wen, W.Y.[Wen-Ying],
Gradient-Guided Single Image Super-Resolution Based on Joint
Trilateral Feature Filtering,
CirSysVideo(33), No. 2, February 2023, pp. 505-520.
IEEE DOI
2302
Kernel, Superresolution, Convolutional neural networks,
Interpolation, Image edge detection, Feature extraction,
deep convolutional neural network
BibRef
Park, K.[Karam],
Soh, J.W.[Jae Woong],
Cho, N.I.[Nam Ik],
A Dynamic Residual Self-Attention Network for Lightweight Single
Image Super-Resolution,
MultMed(25), 2023, pp. 907-918.
IEEE DOI
2303
BibRef
Earlier:
Single Image Super-Resolution with Dynamic Residual Connection,
ICPR21(1-8)
IEEE DOI
2105
Image reconstruction, Computational modeling,
Computational efficiency, Task analysis, Performance evaluation,
Single image super-resolution.
Adaptation models, Architecture, Superresolution,
Benchmark testing, Convolutional neural networks
BibRef
Soh, J.W.[Jae Woong],
Park, G.Y.[Gu Yong],
Jo, J.[Junho],
Cho, N.I.[Nam Ik],
Natural and Realistic Single Image Super-Resolution With Explicit
Natural Manifold Discrimination,
CVPR19(8114-8123).
IEEE DOI
2002
BibRef
Gao, R.[Rui],
Cheng, D.Q.[De-Qiang],
Kou, Q.Q.[Qi-Qi],
Chen, L.L.[Liang-Liang],
Single image super-resolution based on sparse representation using
edge-preserving regularization and a low-rank constraint,
IET-IPR(17), No. 3, 2023, pp. 956-968.
DOI Link
2303
edge-preserving, low-rank constraint,
single image super-resolution,
sparse representation
BibRef
Zandavi, S.M.[Seid Miad],
Post-trained convolution networks for single image super-resolution,
AI(318), 2023, pp. 103882.
Elsevier DOI
2303
CNN, SISR, Post-trained CNN, VDSR
BibRef
An, T.[Tai],
Mao, B.J.[Bin-Jie],
Xue, B.[Bin],
Huo, C.L.[Chun-Lei],
Xiang, S.M.[Shi-Ming],
Pan, C.H.[Chun-Hong],
Patch loss: A generic multi-scale perceptual loss for single image
super-resolution,
PR(139), 2023, pp. 109510.
Elsevier DOI
2304
Single-image super-resolution, Multi-scale loss functions,
Image visual perception, Perceptual metrics
BibRef
Chen, J.C.[Jia-Cheng],
Wang, W.L.[Wan-Liang],
Xing, F.S.[Fang-Sen],
Tu, H.Y.[Hang-Yao],
Multi-feature fusion attention network for single image
super-resolution,
IET-IPR(17), No. 5, 2023, pp. 1389-1402.
DOI Link
2304
attention mechanism, hierarchy feature fusion, multi-scale,
single image super-resolution
BibRef
Liu, Y.Y.[Yuan-Yuan],
Yue, M.[Mengtao],
Yan, H.[Han],
Zhu, L.[Lu],
Single-image super-resolution using lightweight
transformer-convolutional neural network hybrid model,
IET-IPR(17), No. 10, 2023, pp. 2881-2893.
DOI Link
2308
image processing, image reconstruction, image resolution
BibRef
Zhu, H.[Han],
Chen, Z.Z.[Zhen-Zhong],
Liu, S.[Shan],
Learning knowledge representation with meta knowledge distillation
for single image super-resolution,
JVCIR(95), 2023, pp. 103874.
Elsevier DOI
2309
Knowledge distillation, Single image super-resolution,
Representation of knowledge, Meta learning, Texture-aware dynamic kernel
BibRef
Cao, J.F.[Jian-Fang],
Chen, Z.[Zeyu],
Cui, H.Y.[Hong-Yan],
Ji, X.F.[Xiao-Fei],
Wang, X.H.[Xian-Hui],
Liang, Y.C.[Yun-Chuan],
Tian, Y.[Yun],
Improved wavelet prediction superresolution reconstruction based on
U-Net,
IET-IPR(17), No. 12, 2023, pp. 3464-3476.
DOI Link
2310
channel attention, convolutional neural network, deep learning,
single-image superresolution, wavelet transform
BibRef
Hwang, S.[Seongmin],
Han, D.[Daeyoung],
Jeon, M.[Moongu],
Making depthwise convolution SR-friendly via kernel attention
injection,
JVCIR(96), 2023, pp. 103930.
Elsevier DOI
2310
Single image super-resolution (SISR),
Linear depthwise convolution, Kernel attention, Determinant pooling
BibRef
Zou, W.B.[Wen-Bin],
Chen, L.[Liang],
Wu, Y.[Yi],
Zhang, Y.C.[Yun-Chen],
Xu, Y.X.[Yu-Xiang],
Shao, J.[Jun],
Joint Wavelet Sub-Bands Guided Network for Single Image
Super-Resolution,
MultMed(25), 2023, pp. 4623-4637.
IEEE DOI
2311
BibRef
Ding, Q.T.[Qing-Tang],
Liang, Z.Y.[Zheng-Yu],
Wang, L.G.[Long-Guang],
Wang, Y.Q.[Ying-Qian],
Yang, J.G.[Jun-Gang],
Not All Patches Are Equal: Hierarchical Dataset Condensation for
Single Image Super-Resolution,
SPLetters(30), 2023, pp. 1752-1756.
IEEE DOI
2312
BibRef
Chen, J.[Jia],
Wang, L.[Lizhe],
Feng, R.[Ruyi],
Liu, P.[Peng],
Han, W.[Wei],
Chen, X.D.[Xiao-Dao],
CycleGAN-STF: Spatiotemporal Fusion via CycleGAN-Based Image
Generation,
GeoRS(59), No. 7, July 2021, pp. 5851-5865.
IEEE DOI
2106
Spatiotemporal phenomena, Spatial resolution, Remote sensing,
Wavelet transforms, Generative adversarial networks,
wavelet transform
BibRef
Zheng, X.W.[Xiong-Wei],
Feng, R.[Ruyi],
Fan, J.Q.[Jun-Qing],
Han, W.[Wei],
Yu, S.N.[Sheng-Nan],
Chen, J.[Jia],
MSISR-STF: Spatiotemporal Fusion via Multilevel Single-Image
Super-Resolution,
RS(15), No. 24, 2023, pp. 5675.
DOI Link
2401
BibRef
Deepak, A.V.S.,
Ghanekhar, U.[Umesh],
Analysis of Single Image Super-Resolution Techniques:
An Evolutionary Study,
IJIG(24), No. 1, Januaur 2024, pp. 2450002.
DOI Link
2402
BibRef
Chen, Q.Z.[Qi-Zhou],
Shao, Q.[Qing],
Single image super-resolution based on trainable feature matching
attention network,
PR(149), 2024, pp. 110289.
Elsevier DOI Code:
WWW Link.
2403
Super-resolution, Feature matching, Non-local,
Recurrent convolutional neural network, Deep learning
BibRef
Xu, P.C.[Peng-Cheng],
Liu, Q.[Qun],
Bao, H.[Huanan],
Zhang, R.[Ruhui],
Gu, L.H.[Li-Hua],
Wang, G.[Guoyin],
FDSR: An Interpretable Frequency Division Stepwise Process Based
Single-Image Super-Resolution Network,
IP(33), 2024, pp. 1710-1725.
IEEE DOI
2403
Image reconstruction, Frequency conversion, Visualization,
Superresolution, Degradation, Band-pass filters,
step-wise reconstruction
BibRef
Qiao, F.J.[Feng-Juan],
Zhu, Y.G.[Yong-Gui],
Li, G.F.[Guo-Fang],
Li, B.[Bin],
Dual contrastive attention-guided deformable convolutional network
for single image super-resolution,
JVCIR(100), 2024, pp. 104097.
Elsevier DOI
2405
Image super-resolution, Deformable convolution,
Contrastive learning, Attention mechanism
BibRef
Liu, B.Z.[Bing-Zan],
Ning, X.[Xin],
Ma, S.C.[Shi-Chao],
Lian, X.B.[Xia-Bin],
A Lightweight Pyramid Feature Fusion Network for Single Image
Super-Resolution Reconstruction,
SPLetters(31), 2024, pp. 1575-1579.
IEEE DOI
2406
Feature extraction, Convolution, Image reconstruction,
Performance evaluation, Transformers, Training, Kernel,
multi-scale feature fusion
BibRef
Liu, D.[Dong],
Wang, X.F.[Xiao-Feng],
Han, R.D.[Rui-Dong],
Bai, N.N.[Ning-Ning],
Hou, J.P.[Jian-Peng],
Pang, S.[Shanmin],
CTE-Net: Contextual Texture Enhancement Network for Image
Super-Resolution,
MultMed(26), 2024, pp. 8000-8013.
IEEE DOI
2408
Image reconstruction, Feature extraction, Superresolution,
Image restoration, Convolutional neural networks, Correlation,
multi-level feature aggregation
BibRef
Zhou, Y.P.[Yu-Peng],
Li, Z.[Zhen],
Guo, C.L.[Chun-Le],
Bai, S.[Song],
Cheng, M.M.[Ming-Ming],
Hou, Q.[Qibin],
SRFormer: Permuted Self-Attention for Single Image Super-Resolution,
ICCV23(12734-12745)
IEEE DOI Code:
WWW Link.
2401
BibRef
Zhou, H.Y.[Hong-Yang],
Zhu, X.B.[Xia-Bin],
Zhu, J.Q.[Jian-Qing],
Han, Z.[Zheng],
Zhang, S.X.[Shi-Xue],
Qin, J.Y.[Jing-Yan],
Yin, X.C.[Xu-Cheng],
Learning Correction Filter via Degradation-Adaptive Regression for
Blind Single Image Super-Resolution,
ICCV23(12331-12341)
IEEE DOI Code:
WWW Link.
2401
BibRef
Yang, C.X.[Cui-Xin],
Xiao, J.[Jun],
Ju, Y.[YaKun],
Qiu, G.P.[Guo-Ping],
Lam, K.M.[Kin-Man],
Improving Robustness of Single Image Super-Resolution Models with
Monte Carlo Method,
ICIP23(2135-2139)
IEEE DOI Code:
WWW Link.
2312
BibRef
Niu, A.[Axi],
Zhang, K.[Kang],
Pham, T.X.[Trung X.],
Sun, J.Q.[Jin-Qiu],
Zhu, Y.[Yu],
Kweon, I.S.[In So],
Zhang, Y.N.[Yan-Ning],
CDPMSR: Conditional Diffusion Probabilistic Models for Single Image
Super-Resolution,
ICIP23(615-619)
IEEE DOI
2312
BibRef
Sahoo, S.[Subhasmita],
Das, K.[Kinsuk],
Sharma, M.[Mohit],
Sarvesh,
Gadde, R.[Rajnarayana],
Edge Synthesis Block: A Building Unit for Real-Time Single Image
Super Resolution,
ICIP23(915-919)
IEEE DOI
2312
BibRef
Tian, S.[Senmao],
Lu, M.[Ming],
Liu, J.[JiaMing],
Guo, Y.D.[Yan-Dong],
Chen, Y.R.[Yu-Rong],
Zhang, S.[Shunli],
CABM: Content-Aware Bit Mapping for Single Image Super-Resolution
Network with Large Input,
CVPR23(1756-1765)
IEEE DOI
2309
BibRef
Park, S.H.[Seung Ho],
Moon, Y.S.[Young Su],
Cho, N.I.[Nam Ik],
Perception-Oriented Single Image Super-Resolution using Optimal
Objective Estimation,
CVPR23(1725-1735)
IEEE DOI
2309
BibRef
Berger, G.[Guillaume],
Dhingra, M.[Manik],
Mercier, A.[Antoine],
Savani, Y.[Yashesh],
Panchal, S.[Sunny],
Porikli, F.M.[Fatih M.],
QuickSRNet: Plain Single-Image Super-Resolution Architecture for
Faster Inference on Mobile Platforms,
MobileAI23(2187-2196)
IEEE DOI
2309
BibRef
Nguyen, N.L.[Ngoc Long],
Anger, J.[Jérémy],
Davy, A.[Axel],
Arias, P.[Pablo],
Facciolo, G.[Gabriele],
L1BSR: Exploiting Detector Overlap for Self-Supervised Single-Image
Super-Resolution of Sentinel-2 L1B Imagery,
EarthVision23(2013-2023)
IEEE DOI
2309
BibRef
Choong, H.Y.[Han Yao],
Kumar, S.[Suryansh],
Van Gool, L.J.[Luc J.],
Quantum Annealing for Single Image Super-Resolution,
NTIRE23(1150-1159)
IEEE DOI
2309
BibRef
Hu, Z.Q.[Zhi-Qiang],
Yu, T.[Tao],
Learning to Predict Decomposed Dynamic Filters for Single Image Motion
Deblurring,
ACCV22(III:390-408).
Springer DOI
2307
BibRef
Ayazoglu, M.[Mustafa],
Bilecen, B.B.[Bahri Batuhan],
XCAT - Lightweight Quantized Single Image Super-resolution Using
Heterogeneous Group Convolutions and Cross Concatenation,
AIM22(475-488).
Springer DOI
2304
BibRef
Nguyen, Q.H.[Quan H.],
Beksi, W.J.[William J.],
Single Image Super-Resolution via a Dual Interactive Implicit Neural
Network,
WACV23(4925-4934)
IEEE DOI
2302
Adaptation models, Superresolution, Neural networks, Transforms,
Benchmark testing, visual reasoning.
BibRef
Chatillon, P.[Pierrick],
Gousseau, Y.[Yann],
Lefebvre, S.[Sidonie],
A statistically constrained internal method for single image
super-resolution,
ICPR22(1322-1328)
IEEE DOI
2212
Deep learning, Histograms, Image color analysis, Superresolution,
Task analysis, Colored noise
BibRef
Wang, S.Z.[Shi-Zun],
Liu, J.M.[Jia-Ming],
Chen, K.X.[Kai-Xin],
Li, X.Q.[Xiao-Qi],
Lu, M.[Ming],
Guo, Y.D.[Yan-Dong],
Adaptive Patch Exiting for Scalable Single Image Super-Resolution,
ECCV22(XVIII:292-307).
Springer DOI
2211
BibRef
Zhang, Y.H.[Yue-Han],
Ji, B.[Bo],
Hao, J.[Jia],
Yao, A.[Angela],
Perception-Distortion Balanced ADMM Optimization for Single-Image
Super-Resolution,
ECCV22(XVIII:108-125).
Springer DOI
2211
BibRef
Ji, S.W.[Seo-Won],
Lee, J.[Jeongmin],
Kim, S.W.[Seung-Wook],
Hong, J.P.[Jun-Pyo],
Baek, S.J.[Seung-Jin],
Jung, S.W.[Seung-Won],
Ko, S.J.[Sung-Jea],
XYDeblur: Divide and Conquer for Single Image Deblurring,
CVPR22(17400-17409)
IEEE DOI
2210
Performance evaluation, Image color analysis,
Computer architecture, Network architecture, Image restoration,
Computer vision theory
BibRef
Lu, Z.S.[Zhi-Sheng],
Li, J.C.[Jun-Cheng],
Liu, H.[Hong],
Huang, C.Y.[Chao-Yan],
Zhang, L.L.[Lin-Lin],
Zeng, T.Y.[Tie-Yong],
Transformer for Single Image Super-Resolution,
NTIRE22(456-465)
IEEE DOI
2210
Adaptation models, Computational modeling, Superresolution,
Memory management, Graphics processing units, Transformers
BibRef
Cho, S.J.[Sung-Jin],
Ji, S.W.[Seo-Won],
Hong, J.P.[Jun-Pyo],
Jung, S.W.[Seung-Won],
Ko, S.J.[Sung-Jea],
Rethinking Coarse-to-Fine Approach in Single Image Deblurring,
ICCV21(4621-4630)
IEEE DOI
2203
Training, Codes, Stacking, Computer architecture, Image restoration,
Decoding, Low-level and physics-based vision, Computational photography
BibRef
Zuo, Z.M.[Zhe-Ming],
Chen, X.Y.[Xin-Yu],
Xu, H.[Han],
Li, J.[Jie],
Liao, W.J.[Wen-Juan],
Yang, Z.X.[Zhi-Xin],
Wang, S.Z.[Shi-Zheng],
IDEA-Net: Adaptive Dual Self-Attention Network for Single Image
Denoising,
ComputationalApp22(739-748)
IEEE DOI
2202
Training, Adaptive systems, Superresolution, Noise reduction,
Computational efficiency, Noise measurement, Face detection
BibRef
Kar, A.[Aupendu],
Biswas, P.K.[Prabir Kumar],
Fast Bayesian Uncertainty Estimation and Reduction of Batch
Normalized Single Image Super-Resolution Network,
CVPR21(4955-4964)
IEEE DOI
2111
Training, Uncertainty, Superresolution, Estimation, Tools,
Bayes methods, Convolutional neural networks
BibRef
Jo, Y.H.[Young-Hyun],
Kim, S.J.[Seon Joo],
Practical Single-Image Super-Resolution Using Look-Up Table,
CVPR21(691-700)
IEEE DOI
2111
Radio frequency, Interpolation, Visualization, TV, Runtime,
Superresolution, Software
BibRef
Kar, A.[Aupendu],
Dhara, S.K.[Sobhan Kanti],
Sen, D.[Debashis],
Biswas, P.K.[Prabir Kumar],
Zero-shot Single Image Restoration through Controlled Perturbation of
Koschmieder's Model,
CVPR21(16200-16210)
IEEE DOI
2111
Degradation, Training, Perturbation methods, Light scattering,
Data models, Image restoration, Pattern recognition
BibRef
Ayazoglu, M.[Mustafa],
Extremely Lightweight Quantization Robust Real-Time Single-Image
Super Resolution for Mobile Devices,
MAI21(2472-2479)
IEEE DOI
2109
Performance evaluation, Deep learning,
Quantization (signal), Image resolution, Runtime, Computational modeling
BibRef
Du, X.B.[Xiao-Biao],
Niu, J.[Jie],
Liu, C.J.[Chong-Jin],
Expectation-Maximization Attention Cross Residual Network for Single
Image Super-resolution,
UG21(888-896)
IEEE DOI
2109
Deep learning, Convolution, Computational modeling,
Superresolution, Neural networks, Visual effects, Pattern recognition
BibRef
Shi, H.,
Jiang, J.,
Yao, J.,
Xu, Z.,
Single Image Super-Resolution Using Depth Map as Constraint,
ICIP20(538-542)
IEEE DOI
2011
Training, Transforms, Visualization, Feature extraction, Measurement,
Spatial resolution, super-resolution, depth map, feature transform, weight map
BibRef
Su, R.,
Zhong, B.,
Ji, J.,
Ma, K.K.,
Single Image Super-Resolution Via A Progressive Mixture Model,
ICIP20(508-512)
IEEE DOI
2011
Training, Image reconstruction, Mixture models,
Image resolution, Training data, Computational modeling,
progressive mixture model
BibRef
Hussein, S.A.,
Tirer, T.,
Giryes, R.,
Correction Filter for Single Image Super-Resolution: Robustifying
Off-the-Shelf Deep Super-Resolvers,
CVPR20(1425-1434)
IEEE DOI
2008
Kernel, Training, Image reconstruction, Signal resolution,
Spatial resolution, Convolution
BibRef
Cai, J.,
Zeng, H.,
Yong, H.,
Cao, Z.,
Zhang, L.,
Toward Real-World Single Image Super-Resolution:
A New Benchmark and a New Model,
ICCV19(3086-3095)
IEEE DOI
2004
cameras, image registration, image resolution,
learning (artificial intelligence), Benchmark testing
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
Seif, G.,
Androutsos, D.,
Large Receptive Field Networks for High-Scale Image Super-Resolution,
Restoration18(876-87609)
IEEE DOI
1812
Kernel, Image resolution, Convolutional codes, Convolution,
Signal resolution, Memory management
BibRef
Chowdhury, D.,
Androutsos, D.,
Single Image Super-Resolution via Cascaded Parallel Multisize
Receptive Field,
ICIP19(2861-2865)
IEEE DOI
1910
Image Super Resolution, Convolution Neural Network,
Receptive Field, Cascaded Parallel Block, Residual Block
BibRef
Franchi, G.[Gianni],
Yao, A.[Angela],
Kolb, A.[Andreas],
Supervised Deep Kriging for Single-Image Super-Resolution,
GCPR18(638-649).
Springer DOI
1905
BibRef
Huang, J.[Jie],
Zhu, P.F.[Peng-Fei],
Geng, M.R.[Ming-Rui],
Ran, J.W.[Jie-Wen],
Zhou, X.G.[Xing-Guang],
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
BibRef
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
BibRef
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
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
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
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.[Nataa],
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
BibRef
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
BibRef
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
Köhler, T.[Thomas],
Jordan, J.[Johannes],
Maier, A.[Andreas],
Hornegger, J.[Joachim],
A Unified Bayesian Approach to Multi-Frame Super-Resolution and
Single-Image Upsampling in Multi-Sensor Imaging,
BMVC15(xx-yy).
DOI Link
1601
BibRef
Gu, S.,
Meng, D.,
Zuo, W.,
Zhang, L.,
Joint Convolutional Analysis and Synthesis Sparse Representation for
Single Image Layer Separation,
ICCV17(1717-1725)
IEEE DOI
1802
image denoising, image representation, image texture, ASR,
JCAS model, SSR, analysis sparse representation,
Rain
BibRef
Gu, S.,
Zuo, W.,
Xie, Q.,
Meng, D.,
Feng, X.,
Zhang, L.,
Convolutional Sparse Coding for Image Super-Resolution,
ICCV15(1823-1831)
IEEE DOI
1602
Convolution
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
BibRef
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.J.[Le-Jun],
Wu, X.Y.[Xiao-Yu],
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
BibRef
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
BibRef
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
BibRef
Patel, R.C.,
Joshi, M.V.,
Super-resolution of Hyperspectral Images Using Compressive Sensing
Based Approach,
AnnalsPRS(I-7), No. 2012, pp. 83-88.
DOI Link
1209
BibRef
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
BibRef
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
BibRef
Gu, Y.[Ying],
Qu, Y.Y.[Yan-Yun],
Fang, T.Z.[Tian-Zhu],
Li, C.H.[Cui-Hua],
Wang, H.Z.[Han-Zi],
Image super-resolution based on multikernel regression,
ICPR12(2071-2074).
WWW Link.
1302
BibRef
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
BibRef
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.B.[Ke-Bin],
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
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
Ruic, T.[Tijana],
Luong, H.Q.[Hięp Q.],
Piurica, 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 Networks for Single Image Super Resolution .