19.4.3.8 Single Image Super Resolution

Chapter Contents (Back)
Super Resolution. Single Image Super Resolution. Single Image. Learning:
See also Learning, Neural Networks 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
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,
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SK-SVR: Sigmoid kernel support vector regression based in-scale single image super-resolution,
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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,
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IET-CV(11), No. 7, October 2017, pp. 517-529.
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Gong, W.G.[Wei-Guo], Yi, Q.[Qiane], Tang, Y.L.[Yong-Liang], Li, W.H.[Wei-Hong],
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SP:IC(57), No. 1, 2017, pp. 197-210.
Elsevier DOI 1709
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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],
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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.
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Tao, Y.[Yu], Muller, J.P.[Jan-Peter],
Super-Resolution Restoration of Spaceborne Ultra-High-Resolution Images Using the UCL OpTiGAN System,
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Zhang, Q.L.[Qing-Lin], Chen, B.L.[Bing-Ling], Lu, X.[Xuan], Xia, Q.Q.[Qiao-Qiao],
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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
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Zheng, H.B.[Hong-Bo], Ren, L.Y.[Liu-Yan], Ling-Ling, K.[Ke], Qin, X.[Xujia], Zhang, M.Y.[Mei-Yu],
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IET-IPR(13), No. 3, February 2019, pp. 483-490.
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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.J.[Shu-Jin], Li, Y.H.[Yue-Hua],
Single Image Super-Resolution under Multi-Frame Method,
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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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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,
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Brifman, A., Romano, Y., Elad, M.[Michael],
Unified Single-Image and Video Super-Resolution via Denoising Algorithms,
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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,
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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],
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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,
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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,
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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,
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Springer DOI 2005
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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,
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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],
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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,
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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],
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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
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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,
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DOI Link 2105
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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,
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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,
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IEEE DOI 2205
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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],
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DOI Link 2110
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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,
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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
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Chen, R.[Rui], Zhang, Y.[Yan],
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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,
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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.
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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
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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
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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.[Chunhong],
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
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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
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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


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
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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
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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
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
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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.[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

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
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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
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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.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.
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Set5, Set14, Urban 100, BSD 100, Sun-Hays 80 Datasets,
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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
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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
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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
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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
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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
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Trinh, D.H.[Dinh Hoan], Luong, M., Rocchisani, J., Pham, C.D.[Canh Duong], Pham, H.D.[Huy Dien], Dibos, F.,
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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],
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ICPR12(1060-1063).
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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).
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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.
DOI Link 1209
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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
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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
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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],
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ICPR12(1948-1951).
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Gu, Y.[Ying], Qu, Y.Y.[Yan-Yun], Fang, T.Z.[Tian-Zhu], Li, C.H.[Cui-Hua], Wang, H.Z.[Han-Zi],
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ICPR12(2071-2074).
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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).
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Lin, C.Y.[Chun-Yu], Hsu, C.C.[Chih-Chung], Lin, C.W.[Chia-Wen], Kang, L.W.[Li-Wei],
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VCIP11(1-4).
IEEE DOI 1201
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He, H.[He], Siu, W.C.[Wan-Chi],
Single Image Super-Resolution Using Gaussian Process Regression,
CVPR11(449-456).
IEEE DOI 1106
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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
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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
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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
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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
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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
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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
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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
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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 .


Last update:Mar 16, 2024 at 20:36:19