Capel, D.[David],
Image Mosaicing and Super-resolution,
Springer-Verlag2004.
ISBN 1-85233-771-0.
HTML Version.
BibRef
0400
Ph.D.Thesis. Oxford. 2001.
BibRef
Capel, D.[David],
Zisserman, A.[Andrew],
Super-Resolution from Multiple Views Using Learnt Image Models,
CVPR01(II:627-634).
IEEE DOI
0110
BibRef
Earlier:
Super-resolution Enhancement of Text Image Sequences,
ICPR00(Vol I: 600-605).
IEEE DOI
0009
BibRef
Earlier:
Automated Mosaicing with Super-resolution Zoom,
CVPR98(885-891).
IEEE DOI
BibRef
Devaney, A.J.[Anthony J.],
Guo, P.Y.[Peng-Yi],
Superresolution imaging from limited-aperture optical diffracted field
data,
JOSA-A(22), No. 6, June 2005, pp. 1086-1092.
WWW Link.
0601
BibRef
Donaldson, K.[Katherine],
Myers, G.K.[Gregory K.],
Bayesian Super-Resolution of Text in Video with a Text-Specific Bimodal
Prior,
IJDAR(7), No. 2-3, July 2005, pp. 159-167.
Springer DOI
0508
BibRef
Earlier:
CVPR05(I: 1188-1195).
IEEE DOI
0507
BibRef
Mancas-Thillou, C.[Céline],
Ferreira, S.[Silvio],
Gosselin, B.[Bernard],
An Embedded Application for Degraded Text Recognition,
JASP(2005), No. 13, 2005, pp. 2127-2135.
WWW Link.
0603
BibRef
Mancas-Thillou, C.,
Mancas, M.,
Gosselin, B.,
Camera-based degraded character segmentation into individual components,
ICDAR05(II: 755-759).
IEEE DOI
0508
BibRef
Sroubek, F.,
Cristobal, G.,
Flusser, J.,
A Unified Approach to Superresolution and Multichannel Blind
Deconvolution,
IP(16), No. 9, September 2007, pp. 2322-2332.
IEEE DOI
0709
BibRef
Sroubek, F.[Filip],
Flusser, J.[Jan],
Resolution enhancement via probabilistic deconvolution of multiple
degraded images,
PRL(27), No. 4, March 2006, pp. 287-293.
Elsevier DOI
0602
BibRef
Earlier:
Registration and Fusion of Blurred Images,
ICIAR04(I: 122-129).
Springer DOI
0409
Image fusion; Multichannel blind deconvolution;
Image registration; MAP estimator
BibRef
Walha, R.[Rim],
Drira, F.[Fadoua],
Lebourgeois, F.[Franck],
Alimi, A.M.[Adel M.],
Garcia, C.[Christophe],
Resolution enhancement of textual images:
a survey of single image-based methods,
IET-IPR(10), No. 4, 2016, pp. 325-337.
DOI Link
1604
BibRef
Earlier: A1, A2, A3, A5, A4:
Sparse Coding with a Coupled Dictionary Learning Approach for Textual
Image Super-resolution,
ICPR14(4459-4464)
IEEE DOI
1412
BibRef
Earlier:
Multiple Learned Dictionaries Based Clustered Sparse Coding for the
Super-Resolution of Single Text Image,
ICDAR13(484-488)
IEEE DOI
1312
character recognition.
Dictionaries
BibRef
Walha, R.[Rim],
Drira, F.[Fadoua],
Lebourgeois, F.[Frank],
Garcia, C.[Christophe],
Alimi, A.M.[Adel M.],
Resolution enhancement of textual images via multiple coupled
dictionaries and adaptive sparse representation selection,
IJDAR(18), No. 1, March 2015, pp. 87-107.
Springer DOI
1503
BibRef
Walha, R.[Rim],
Drira, F.[Fadoua],
Lebourgeois, F.[Frank],
Garcia, C.[Christophe],
Alimi, A.M.[Adel M.],
Handling noise in textual image resolution enhancement using online and
offline learned dictionaries,
IJDAR(21), No. 1-2, June 2018, pp. 137-157.
Springer DOI
1806
BibRef
Earlier:
Joint denoising and magnification of noisy Low-Resolution textual
images,
ICDAR15(871-875)
IEEE DOI
1511
BibRef
Walha, R.[Rim],
Drira, F.[Fadoua],
Lebourgeois, F.[Franck],
Single Textual Image Super-Resolution Using Multiple Learned
Dictionaries Based Sparse Coding,
CIAP13(II:439-448).
Springer DOI
1309
BibRef
Abedi, A.[Ali],
Kabir, E.[Ehsanollah],
Text-image super-resolution through anchored neighborhood regression
with multiple class-specific dictionaries,
SIViP(11), No. 2, February 2017, pp. 275-282.
WWW Link.
1702
BibRef
Ma, J.Q.[Jian-Qi],
Guo, S.[Shi],
Zhang, L.[Lei],
Text Prior Guided Scene Text Image Super-Resolution,
IP(32), 2023, pp. 1341-1353.
IEEE DOI
2303
Text recognition, Superresolution, Visualization, Image resolution,
Generators, Feature extraction, text prior
BibRef
Ma, J.Q.[Jian-Qi],
Liang, Z.T.[Zhe-Tong],
Xiang, W.M.[Wang-Meng],
Yang, X.[Xi],
Zhang, L.[Lei],
A Benchmark for Chinese-English Scene Text Image Super-resolution,
ICCV23(19395-19404)
IEEE DOI Code:
WWW Link.
2401
BibRef
Ma, J.Q.[Jian-Qi],
Liang, Z.T.[Zhe-Tong],
Zhang, L.[Lei],
A Text Attention Network for Spatial Deformation Robust Scene Text
Image Super-resolution,
CVPR22(5901-5910)
IEEE DOI
2210
Visualization, Text analysis, Text recognition, Superresolution,
Semantics, Transformers, Convolutional neural networks,
Document analysis and understanding
BibRef
Lat, A.,
Jawahar, C.V.,
Enhancing OCR Accuracy with Super Resolution,
ICPR18(3162-3167)
IEEE DOI
1812
Image resolution, Optical character recognition software,
Training, Interpolation, Image segmentation, Image color analysis, Generators
BibRef
Biswas, C.,
Mukherjee, P.S.,
Ghosh, K.,
Bhattacharya, U.,
Parui, S.K.,
A Hybrid Deep Architecture for Robust Recognition of Text Lines of
Degraded Printed Documents,
ICPR18(3174-3179)
IEEE DOI
1812
Image segmentation, Optical character recognition software,
Text recognition, Databases, Image recognition, Degradation, Engines
BibRef
Zhang, H.,
Liu, D.,
Xiong, Z.,
CNN-based text image super-resolution tailored for OCR,
VCIP17(1-4)
IEEE DOI
1804
convolution, feedforward neural nets, image resolution,
optical character recognition, text analysis, CNN, OCR,
Super-resolution
BibRef
Guo, Y.,
Lu, C.,
Allebach, J.P.,
Bouman, C.A.,
Model-Based Iterative Restoration for Binary Document Image
Compression with Dictionary Learning,
CVPR17(606-615)
IEEE DOI
1711
Cost function, Dictionaries, Entropy, Image coding,
Image restoration, Noise measurement, Standards
BibRef
Yu, X.[Xiang],
Luo, Y.P.[Yu-Pin],
Stratification-based super-resolution algorithm for document
processing,
ICIVC17(766-772)
IEEE DOI
1708
Character recognition, Image edge detection, Image resolution,
Training, document image, example-based, guided filter, real-time, stratification
BibRef
Peyrard, C.[Clement],
Baccouche, M.[Moez],
Mamalet, F.[Franck],
Garcia, C.[Christophe],
ICDAR2015 competition on Text Image Super-Resolution,
ICDAR15(1201-1205)
IEEE DOI
1511
BibRef
An, L.[Le],
Thakoor, N.[Ninad],
Bhanu, B.[Bir],
Vehicle logo super-resolution by canonical correlation analysis,
ICIP12(2229-2232).
IEEE DOI
1302
BibRef
Maruyama, M.[Minoru],
Yamaguchi, T.[Takuma],
Extraction of Characters on Signboards in Natural Scene Images by Stump
Classifiers,
ICDAR09(1365-1369).
IEEE DOI
0907
BibRef
Kato, Y.J.[Yu-Ji],
Deguchi, D.[Daisuke],
Takahashi, T.[Tomokazu],
Ide, I.[Ichiro],
Murase, H.[Hiroshi],
Low Resolution QR-Code Recognition by Applying Super-Resolution Using
the Property of QR-Codes,
ICDAR11(992-996).
IEEE DOI
1111
BibRef
Ohkura, A.[Ataru],
Deguchi, D.[Daisuke],
Ohkura, T.A.[Tomokazu< A1>Ataru],
Deguchi, D.[Daisuke],
Takahashi, T.[Tomokazu],
Ide, I.[Ichiro],
Murase, H.[Hiroshi],
Low-Resolution Character Recognition by Video-Based Super-Resolution,
ICDAR09(191-195).
IEEE DOI
0907
BibRef
Corduneanu, A.,
Platt, J.C.,
Learning Spatially-Variable Filters for Super-Resolution of Text,
ICIP05(I: 849-852).
IEEE DOI
0512
BibRef
Nomura, M.,
Yamamoto, K.,
Ohta, H.,
Kato, K.,
A proposal of the effective recognition method for low-resolution
characters from motion images,
ICDAR05(II: 720-724).
IEEE DOI
0508
BibRef
Dalley, G.,
Freeman, B.,
Marks, J.,
Single-frame text super-resolution: a bayesian approach,
ICIP04(V: 3295-3298).
IEEE DOI
0505
BibRef
Li, H.P.[Hui-Ping],
Doermann, D.S.[David S.],
Superresolution-based Enhancement of Text in Digital Video,
ICPR00(Vol I: 847-850).
IEEE DOI
0009
BibRef
Chapter on OCR, Document Analysis and Character Recognition Systems continues in
Document Image Quality Evaluation .