Zhang, D.[Di],
Li, H.F.[Hui-Fang],
Du, M.H.[Ming-Hui],
Fast MAP-based multiframe super-resolution image reconstruction,
IVC(23), No. 7, 1 July 2005, pp. 671-679.
Elsevier DOI
0506
See also Morphable model space based face super-resolution reconstruction and recognition.
BibRef
Zhang, D.[Di],
Du, M.H.[Ming-Hui],
High-resolution image reconstruction using joint constrained edge
pattern recognition and POCS formulation,
ICARCV04(II: 832-837).
IEEE DOI
0412
BibRef
Yuan, Q.Q.[Qiang-Qiang],
Zhang, L.P.[Liang-Pei],
Shen, H.F.[Huan-Feng],
Multiframe Super-Resolution Employing a Spatially Weighted Total
Variation Model,
CirSysVideo(22), No. 3, March 2012, pp. 379-392.
IEEE DOI
1203
See also Stripe Noise Separation and Removal in Remote Sensing Images by Consideration of the Global Sparsity and Local Variational Properties.
BibRef
Guo, X.[Xian],
Huang, X.[Xin],
Zhang, L.P.[Liang-Pei],
Zhang, L.F.[Le-Fei],
Hyperspectral Image Noise Reduction Based on Rank-1 Tensor
Decomposition,
PandRS(83), No. 1, 2013, pp. 50-63.
Elsevier DOI
1308
Image Restoration.
Tensor decomposition
See also modified stochastic neighbor embedding for multi-feature dimension reduction of remote sensing images, A.
BibRef
Zhang, H.Y.[Hong-Yan],
He, W.[Wei],
Zhang, L.P.[Liang-Pei],
Shen, H.F.[Huan-Feng],
Yuan, Q.,
Hyperspectral Image Restoration Using Low-Rank Matrix Recovery,
GeoRS(52), No. 8, August 2014, pp. 4729-4743.
IEEE DOI
1403
Gaussian noise
BibRef
Zhang, H.Y.[Hong-Yan],
Cai, J.Y.[Jing-Yi],
He, W.[Wei],
Shen, H.F.[Huan-Feng],
Zhang, L.P.[Liang-Pei],
Double Low-Rank Matrix Decomposition for Hyperspectral Image
Denoising and Destriping,
GeoRS(60), 2022, pp. 1-19.
IEEE DOI
2112
Noise reduction, Matrix decomposition, Sparse matrices,
Gaussian noise, TV, Data models, Solid modeling, Denoising, destriping,
low-rank constraint
BibRef
He, W.[Wei],
Zhang, H.Y.[Hong-Yan],
Zhang, L.P.[Liang-Pei],
Shen, H.F.[Huan-Feng],
Total-Variation-Regularized Low-Rank Matrix Factorization for
Hyperspectral Image Restoration,
GeoRS(54), No. 1, January 2016, pp. 178-188.
IEEE DOI
1601
hyperspectral imaging
BibRef
Zheng, Y.B.[Yu-Bang],
Huang, T.Z.[Ting-Zhu],
Zhao, X.L.[Xi-Le],
Chen, Y.[Yong],
He, W.[Wei],
Double-Factor-Regularized Low-Rank Tensor Factorization for Mixed
Noise Removal in Hyperspectral Image,
GeoRS(58), No. 12, December 2020, pp. 8450-8464.
IEEE DOI
2012
Image restoration, Tensors, Gray-scale,
Principal component analysis, Matrix decomposition,
proximal alternating minimization (PAM)
See also Weighted Low-Rank Tensor Recovery for Hyperspectral Image Restoration.
BibRef
He, W.[Wei],
Zhang, H.Y.[Hong-Yan],
Zhang, L.P.[Liang-Pei],
Total Variation Regularized Reweighted Sparse Nonnegative Matrix
Factorization for Hyperspectral Unmixing,
GeoRS(55), No. 7, July 2017, pp. 3909-3921.
IEEE DOI
1706
Adaptation models, Hyperspectral imaging, Minimization, Robustness,
Sparse matrices, TV, Blind unmixing, hyperspectral image,
nonnegative matrix factorization (NMF), reweighted sparsity,
total, variation, (TV)
BibRef
Chen, Y.[Yong],
Huang, T.Z.[Ting-Zhu],
He, W.[Wei],
Yokoya, N.[Naoto],
Zhao, X.L.[Xi-Le],
Hyperspectral Image Compressive Sensing Reconstruction Using
Subspace-Based Nonlocal Tensor Ring Decomposition,
IP(29), 2020, pp. 6813-6828.
IEEE DOI
2007
Tensile stress, Correlation, Image coding, Image reconstruction, TV,
Computational efficiency, Dictionaries, Compressive sensing,
tensor ring decomposition
BibRef
Chen, Y.[Yong],
He, W.[Wei],
Yokoya, N.[Naoto],
Huang, T.Z.[Ting-Zhu],
Zhao, X.L.[Xi-Le],
Nonlocal Tensor-Ring Decomposition for Hyperspectral Image Denoising,
GeoRS(58), No. 2, February 2020, pp. 1348-1362.
IEEE DOI
2001
Noise reduction, Correlation, Matrix decomposition,
Hyperspectral imaging, Data models, Denoising,
tensor-ring (TR) decomposition
BibRef
He, W.[Wei],
Yokoya, N.[Naoto],
Yuan, L.H.[Long-Hao],
Zhao, Q.B.[Qi-Bin],
Remote Sensing Image Reconstruction Using Tensor Ring Completion and
Total Variation,
GeoRS(57), No. 11, November 2019, pp. 8998-9009.
IEEE DOI
1911
Image reconstruction, Matrix decomposition, TV, Remote sensing,
Cloud computing, MODIS, Cloud removal, gap filling, reconstruction,
total variation (TV)
BibRef
Zhang, H.Y.[Hong-Yan],
Liu, L.[Lu],
He, W.[Wei],
Zhang, L.P.[Liang-Pei],
Hyperspectral Image Denoising With Total Variation Regularization and
Nonlocal Low-Rank Tensor Decomposition,
GeoRS(58), No. 5, May 2020, pp. 3071-3084.
IEEE DOI
2005
Noise reduction, TV, Hyperspectral imaging, Image restoration,
Gaussian noise, Denoising, Hyperspectral image (HSI),
tensor decomposition
BibRef
Zhang, H.Y.[Hong-Yan],
Chen, H.Y.[Hong-Yu],
Yang, G.Y.[Guang-Yi],
Zhang, L.P.[Liang-Pei],
LR-Net: Low-Rank Spatial-Spectral Network for Hyperspectral Image
Denoising,
IP(30), 2021, pp. 8743-8758.
IEEE DOI
2111
Noise reduction, Convolution,
Image reconstruction, Hyperspectral imaging, Feature extraction,
multi-scale features
BibRef
Yuan, Q.Q.[Qiang-Qiang],
Zhang, L.P.[Liang-Pei],
Shen, H.F.[Huan-Feng],
Hyperspectral Image Denoising Employing a Spectral-Spatial Adaptive
Total Variation Model,
GeoRS(50), No. 10, October 2012, pp. 3660-3677.
IEEE DOI
1210
BibRef
Shi, Q.[Qian],
Tang, X.P.[Xiao-Pei],
Yang, T.[Taoru],
Liu, R.[Rong],
Zhang, L.P.[Liang-Pei],
Hyperspectral Image Denoising Using a 3-D Attention Denoising Network,
GeoRS(59), No. 12, December 2021, pp. 10348-10363.
IEEE DOI
2112
Noise reduction, Feature extraction, Convolution, Task analysis,
Correlation, Kernel, Noise measurement, Atrous convolution,
self-attention
BibRef
Yuan, Q.Q.[Qiang-Qiang],
Zhang, L.P.[Liang-Pei],
Shen, H.F.[Huan-Feng],
Hyperspectral Image Denoising With a Spatial-Spectral View Fusion
Strategy,
GeoRS(52), No. 5, May 2014, pp. 2314-2325.
IEEE DOI
1403
Adaptation models
BibRef
Yuan, Q.Q.[Qiang-Qiang],
Zhang, L.P.[Liang-Pei],
Shen, H.F.[Huan-Feng],
Regional Spatially Adaptive Total Variation Super-Resolution
with Spatial Information Filtering and Clustering,
IP(22), No. 6, 2013, pp. 2327-2342.
IEEE DOI
1307
k-means clustering, Image edge detection
BibRef
Li, J.[Jie],
Yuan, Q.Q.[Qiang-Qiang],
Shen, H.F.[Huan-Feng],
Zhang, L.P.[Liang-Pei],
Noise Removal From Hyperspectral Image With Joint Spectral-Spatial
Distributed Sparse Representation,
GeoRS(54), No. 9, September 2016, pp. 5425-5439.
IEEE DOI
1609
compressed sensing
BibRef
Yuan, Q.Q.[Qiang-Qiang],
Zhang, Q.[Qiang],
Li, J.[Jie],
Shen, H.F.[Huan-Feng],
Zhang, L.P.[Liang-Pei],
Hyperspectral Image Denoising Employing a Spatial-Spectral Deep
Residual Convolutional Neural Network,
GeoRS(57), No. 2, February 2019, pp. 1205-1218.
IEEE DOI
1901
Noise reduction, Feature extraction, Noise measurement,
Hyperspectral imaging, Image denoising,
multiscale feature extraction
BibRef
Zhang, Q.[Qiang],
Yuan, Q.Q.[Qiang-Qiang],
Li, J.[Jie],
Liu, X.X.[Xin-Xin],
Shen, H.F.[Huan-Feng],
Zhang, L.P.[Liang-Pei],
Hybrid Noise Removal in Hyperspectral Imagery with a Spatial-Spectral
Gradient Network,
GeoRS(57), No. 10, October 2019, pp. 7317-7329.
IEEE DOI
1910
convolutional neural nets, feature extraction,
geophysical image processing, gradient methods,
spatial-spectral
BibRef
Chan, T.M.[Tak-Ming],
Zhang, J.P.[Jun-Ping],
Pu, J.[Jian],
Huang, H.[Hua],
Neighbor embedding based super-resolution algorithm through edge
detection and feature selection,
PRL(30), No. 5, 1 April 2009, pp. 494-502.
Elsevier DOI
0903
BibRef
Earlier: A1, A2, Only:
An Improved Super-Resolution with Manifold Learning and Histogram
Matching,
ICB06(756-762).
Springer DOI
0601
Super-resolution, Neighbor embedding, Feature selection, Image processing
BibRef
Pu, J.[Jian],
Zhang, J.P.[Jun-Ping],
Guo, P.H.[Pei-Hong],
Yuan, X.R.[Xiao-Ru],
Interactive Super-Resolution through Neighbor Embedding,
ACCV09(III: 496-505).
Springer DOI
0909
BibRef
Purkait, P.[Pulak],
Chanda, B.[Bhabatosh],
Super Resolution Image Reconstruction Through Bregman Iteration Using
Morphologic Regularization,
IP(21), No. 9, September 2012, pp. 4029-4039.
IEEE DOI
1208
BibRef
Purkait, P.[Pulak],
Chanda, B.[Bhabatosh],
Morphologic gain-controlled regularization for edge-preserving
super-resolution image reconstruction,
SIViP(7), No. 5, September 2013, pp. 925-938.
WWW Link.
1309
BibRef
Purkait, P.[Pulak],
Chanda, B.[Bhabatosh],
Image Upscaling Using Multiple Dictionaries of Natural Image Patches,
ACCV12(III:284-295).
Springer DOI
1304
BibRef
Wang, L.,
Xiang, S.,
Meng, G.,
Wu, H.,
Pan, C.,
Edge-Directed Single-Image Super-Resolution Via Adaptive Gradient
Magnitude Self-Interpolation,
CirSysVideo(23), No. 8, 2013, pp. 1289-1299.
IEEE DOI
1308
Estimation
BibRef
Turgay, E.[Emre],
Akar, G.B.[Gozde B.],
Texture and edge preserving multiframe super-resolution,
IET-IPR(8), No. 9, September 2014, pp. 499-508.
DOI Link
1410
BibRef
Earlier:
Texture preserving multi frame super resolution with spatially varying
image prior,
ICIP12(2205-2208).
IEEE DOI
1302
BibRef
Earlier:
Context based super resolution image reconstruction,
LNLA09(54-61).
IEEE DOI
0908
Gabor filters
BibRef
Mosleh, A.[Ali],
Bouguila, N.[Nizar],
Ben Hamza, A.,
Image and video spatial super-resolution via bandlet-based sparsity
regularization and structure tensor,
SP:IC(30), No. 1, 2015, pp. 137-146.
Elsevier DOI
1412
Bandlets
See also Bandlet-based sparsity regularization in video inpainting.
BibRef
Yan, Q.[Qing],
Xu, Y.[Yi],
Yang, X.K.[Xiao-Kang],
Nguyen, T.Q.,
Single Image Superresolution Based on Gradient Profile Sharpness,
IP(24), No. 10, October 2015, pp. 3187-3202.
IEEE DOI
1507
Global Positioning System
BibRef
Yan, Q.[Qing],
Xu, Y.[Yi],
Yang, X.K.[Xiao-Kang],
Chen, K.[Kai],
Image Super-Resolution Based on a Novel Edge Sharpness Prior,
ICPR12(1056-1059).
WWW Link.
1302
BibRef
Kim, Y.,
Oh, H.,
Bilgin, A.,
Super resolution reconstruction based on block matching and
three-dimensional filtering with sharpening,
IET-IPR(9), No. 12, 2015, pp. 1048-1056.
DOI Link
1512
adaptive filters
BibRef
Yeganli, F.,
Nazzal, M.,
Ozkaramanli, H.,
Image super-resolution via sparse representation over multiple learned
dictionaries based on edge sharpness and gradient phase angle,
SIViP(9), No. 1 Supp, December 2015, pp. 285-293.
WWW Link.
1601
BibRef
Yeganli, F.,
Nazzal, M.,
Unal, M.,
Ozkaramanli, H.,
Image super-resolution via sparse representation over multiple learned
dictionaries based on edge sharpness,
SIViP(10), No. 3, March 2016, pp. 535-542.
WWW Link.
1602
BibRef
Singh, A.[Abhishek],
Ahuja, N.[Narendra],
Learning ramp transformation for single image super-resolution,
CVIU(135), No. 1, 2015, pp. 109-125.
Elsevier DOI
1504
BibRef
Earlier:
Single image super-resolution using adaptive domain transformation,
ICIP13(947-951)
IEEE DOI
1402
Super-resolution.
Image edge detection
BibRef
Singh, A.[Abhishek],
Porikli, F.M.[Fatih M.],
Ahuja, N.[Narendra],
Super-resolving Noisy Images,
CVPR14(2846-2853)
IEEE DOI
1409
denoising, super-resolution
BibRef
Li, X.,
He, H.,
Wang, R.,
Tao, D.,
Single Image Superresolution via Directional Group Sparsity and
Directional Features,
IP(24), No. 9, September 2015, pp. 2874-2888.
IEEE DOI
1506
Dictionaries
BibRef
Ferreira, J.C.,
Vural, E.,
Guillemot, C.[Christine],
Geometry-Aware Neighborhood Search for Learning Local Models for
Image Superresolution,
IP(25), No. 3, March 2016, pp. 1354-1367.
IEEE DOI
1602
Adaptation models
BibRef
Mandal, S.[Srimanta],
Sao, A.K.[Anil Kumar],
Employing structural and statistical information to learn
dictionary(s) for single image super-resolution in sparse domain,
SP:IC(48), No. 1, 2016, pp. 63-80.
Elsevier DOI
1609
BibRef
Earlier:
Edge preserving single image super resolution in sparse environment,
ICIP13(967-971)
IEEE DOI
1402
Dictionaries
BibRef
And:
Image deblurring in super-resolution framework,
NCVPRIPG13(1-4)
IEEE DOI
1408
Sparse representation.
image enhancement
BibRef
Sidike, P.[Paheding],
Krieger, E.[Evan],
Alom, M.Z.[M. Zahangir],
Asari, V.K.[Vijayan K.],
Taha, T.[Tarek],
A fast single-image super-resolution via directional edge-guided
regularized extreme learning regression,
SIViP(11), No. 5, July 2017, pp. 961-968.
Springer DOI
1706
BibRef
Vassilo, K.[Kyle],
Heatwole, C.[Cory],
Taha, T.[Tarek],
Mehmood, A.[Asif],
Multi-Step Reinforcement Learning for Single Image Super-Resolution,
NTIRE20(2160-2168)
IEEE DOI
2008
Image resolution, Image color analysis,
Task analysis, Image restoration, Standards, Image reconstruction
BibRef
Chen, H.,
He, X.,
Qing, L.,
Teng, Q.,
Single Image Super-Resolution via Adaptive Transform-Based Nonlocal
Self-Similarity Modeling and Learning-Based Gradient Regularization,
MultMed(19), No. 8, August 2017, pp. 1702-1717.
IEEE DOI
1708
Adaptation models, Estimation, Image edge detection,
Image reconstruction, Image resolution, Interpolation, Transforms,
Image super-resolution, Split Bregman Iteration,
gradient regularization, local structure-adaptive transform,
nonlocal, self-similarity
BibRef
Mousavi, H.S.,
Monga, V.,
Sparsity-Based Color Image Super Resolution via Exploiting Cross
Channel Constraints,
IP(26), No. 11, November 2017, pp. 5094-5106.
IEEE DOI
1709
BibRef
Earlier:
Sparsity based super resolution using color channel constraints,
ICIP16(579-583)
IEEE DOI
1610
correlation methods,
image resolution, optimisation,
analogous HR dictionary, color channels,
dictionary learning method, edge similarities,
image quality metrics,
luminance channel information,
sparsity-based color image super resolution,
Dictionaries, Image color analysis, Image edge detection,
Image reconstruction, Spatial resolution, Color super resolution,
single-image super resolution, sparse coding
BibRef
Yang, W.H.[Wen-Han],
Feng, J.S.[Jia-Shi],
Yang, J.C.[Jian-Chao],
Zhao, F.[Fang],
Liu, J.Y.[Jia-Ying],
Guo, Z.M.[Zong-Ming],
Yan, S.C.[Shui-Cheng],
Deep Edge Guided Recurrent Residual Learning for Image
Super-Resolution,
IP(26), No. 12, December 2017, pp. 5895-5907.
IEEE DOI
1710
Feature extraction, Image edge detection, Image reconstruction,
Image resolution, Signal resolution, Training, Super-resolution,
edge guidance, recurrent residual network, sub-band, recovery
BibRef
Ahmed, J.[Junaid],
Waqas, M.[Muhammad],
Ali, S.[Shamshad],
Memon, R.A.[Raheel Ahmed],
Klette, R.[Reinhard],
Coupled dictionary learning in wavelet domain for Single-Image
Super-Resolution,
SIViP(12), No. 3, March 2018, pp. 453-461.
Springer DOI
1804
BibRef
Earlier: A1, A5, Only:
Coupled multiple dictionary learning based on edge sharpness for
single-image super-resolution,
ICPR16(3838-3843)
IEEE DOI
1705
Clustering algorithms, Dictionaries, Image reconstruction,
Image resolution, Signal resolution, Sparse matrices, Training
BibRef
Hou, B.,
Zhou, K.,
Jiao, L.,
Adaptive Super-Resolution for Remote Sensing Images Based on Sparse
Representation With Global Joint Dictionary Model,
GeoRS(56), No. 4, April 2018, pp. 2312-2327.
IEEE DOI
1804
Adaptation models, Dictionaries, Image edge detection,
Image reconstruction, Image resolution, Interpolation,
super-resolution (SR)
BibRef
Zhao, J.W.[Jian-Wei],
Hu, H.P.[He-Ping],
Zhou, Z.H.[Zheng-Hua],
Cao, F.L.[Fei-Long],
Super-resolution reconstruction:
Using non-local structure similarity and edge sharpness dictionary,
IET-IPR(11), No. 12, Decmeber 2017, pp. 1254-1264.
DOI Link
1712
BibRef
Li, K.Q.[Ke-Qiuyin],
Cao, F.L.[Fei-Long],
Super-resolution using neighbourhood regression with local structure
prior,
SP:IC(72), 2019, pp. 58-68.
Elsevier DOI
1902
Super-resolution, Clustering, Regression, Structure prior
BibRef
Nathan, S.[Sabari],
Kansal, P.[Priya],
Leveraging Multi scale Backbone with Multilevel supervision for
Thermal Image Super Resolution,
PBVS21(4327-4333)
IEEE DOI
2109
BibRef
Earlier: A2, A1:
A Multi-Level Supervision Model:
A novel approach for Thermal Image Super Resolution,
PBVS20(426-431)
IEEE DOI
2008
Training, Convolution, Superresolution,
Computer architecture, Robustness, Pattern recognition.
Spatial resolution, Training, Task analysis,
Image edge detection, Convolution
BibRef
Zhou, Y.,
Deng, W.,
Tong, T.,
Gao, Q.,
Guided Frequency Separation Network for Real-World SuperResolution,
NTIRE20(1722-1731)
IEEE DOI
2008
Image color analysis, Image edge detection, Image resolution,
Generators, Training
BibRef
Ma, C.,
Rao, Y.,
Cheng, Y.,
Chen, C.,
Lu, J.,
Zhou, J.,
Structure-Preserving Super Resolution With Gradient Guidance,
CVPR20(7766-7775)
IEEE DOI
2008
Image resolution, Image edge detection, Distortion,
Image reconstruction, Image restoration, Visualization
BibRef
Chen, C.[Chang],
Xiong, Z.W.[Zhi-Wei],
Tian, X.[Xinmei],
Wu, F.[Feng],
Deep Boosting for Image Denoising,
ECCV18(XI: 3-19).
Springer DOI
1810
BibRef
Earlier: A1, A3, A4, A2:
UDNet: Up-Down Network for Compact and Efficient Feature
Representation in Image Super-Resolution,
CEFR-LCV17(1069-1076)
IEEE DOI
1802
Acceleration, Convolution, Feature extraction,
Image reconstruction, Image resolution, Interpolation, Real-time systems
BibRef
Tai, Y.[Ying],
Yang, J.[Jian],
Liu, X.M.[Xiao-Ming],
Xu, C.,
MemNet: A Persistent Memory Network for Image Restoration,
ICCV17(4549-4557)
IEEE DOI
1802
image coding, image denoising, image resolution, image restoration,
learning (artificial intelligence), neural nets, JPEG deblocking,
Transform coding
BibRef
Tai, Y.[Ying],
Yang, J.[Jian],
Liu, X.M.[Xiao-Ming],
Image Super-Resolution via Deep Recursive Residual Network,
CVPR17(2790-2798)
IEEE DOI
1711
Computational modeling, Convolution, Convolutional codes,
Image resolution, Image restoration, Neural networks, Training
BibRef
Shibata, T.,
Sato, A.,
Single image super resolution based on content-aware constraint and
intensity-order constraint,
MVA17(153-156)
DOI Link
1708
Eigenvalues and eigenfunctions, Image edge detection,
Image reconstruction, Image resolution, Organizations, TV, Training
BibRef
Wang, R.[Ruxin],
Han, C.Y.[Cong-Ying],
Li, M.Q.[Ming-Qiang],
Guo, T.D.[Tian-De],
Single Image Super-Resolution Reconstruction Based on Edge-Preserving
with External and Internal Gradient Prior Knowledge,
NTIRE16(I: 191-205).
Springer DOI
1704
BibRef
Xia, L.Y.,
Lin, X.X.,
Liang, Y.,
Jiang, H.K.,
Chai, H.,
Huang, H.H.,
Image Super-Resolution Reconstruction via L1_2 and S1_2
Regularizations,
DICTA16(1-8)
IEEE DOI
1701
Image edge detection
BibRef
Chen, Z.,
Muramatsu, S.,
Abe, Y.,
Fast image super-resolution via multiple directional transforms,
ICIP16(1434-1438)
IEEE DOI
1610
Image edge detection
BibRef
Su, C.[Chang],
Tao, L.[Li],
Fast single-image upsampling with relative edge growth rate priors,
ICIP15(3876-3880)
IEEE DOI
1512
Image upsampling
BibRef
Krishnan, S.[Shankar],
Klosowski, J.T.[James T.],
Guided image upsampling using bitmap tracing,
ICIP13(650-654)
IEEE DOI
1402
Image edge detection
BibRef
Xi, H.Q.[Hui-Qin],
Xiao, C.B.[Chuang-Bai],
Bian, C.X.[Chun-Xiao],
Edge Halo Reduction for Projections onto Convex Sets Super Resolution
Image Reconstruction,
DICTA12(1-7).
IEEE DOI
1303
BibRef
Kang, W.S.[Won-Seok],
Jeon, J.H.[Jae-Hwan],
Lee, E.S.[Eun-Sung],
Cho, C.H.[Chang-Hun],
Jung, J.H.[Jung-Hoon],
Kim, T.C.[Tae-Chan],
Katsaggelos, A.K.[Aggelos K.],
Paik, J.[Joonki],
Real-time super-resolution for digital zooming using finite
kernel-based edge orientation estimation and truncated image
restoration,
ICIP13(1311-1315)
IEEE DOI
1402
Estimation
BibRef
Jeon, J.H.[Jae-Hwan],
Lee, J.H.[Jin-Hee],
Lee, E.S.[Eun-Sung],
Hayes, M.H.[Monson H.],
Paik, J.K.[Joon-Ki],
Regularized adaptive super-resolution using kernel estimation-based
edge reconnection and kernel orientation constraints,
ICIP12(2213-2216).
IEEE DOI
1302
BibRef
Fan, Y.Q.[Ya-Qiong],
Gan, Z.L.[Zong-Liang],
Qiu, Y.[Yiwen],
Zhu, X.C.[Xiu-Chang],
Single Image Super Resolution Method Based on Edge Preservation,
ICIG11(394-399).
IEEE DOI
1109
BibRef
Bie, H.X.[Hong Xia],
Liu, C.Y.[Chen Yi],
Edge-Directed Sub-Pixel Extraction and Still Image Super-Resolution,
CISP09(1-4).
IEEE DOI
0910
BibRef
Tai, Y.W.[Yu-Wing],
Tong, W.S.[Wai-Shun],
Tang, C.K.[Chi-Keung],
Perceptually-Inspired and Edge-Directed Color Image Super-Resolution,
CVPR06(II: 1948-1955).
IEEE DOI
0606
BibRef
Jung, C.H.[Chan-Ho],
Kim, G.H.[Gyeong-Hwan],
An Iterative Method for Preserving Edges and Reducing Noise in High
Resolution Image Reconstruction,
ACCV06(II:325-334).
Springer DOI
0601
Enhance resolution.
BibRef
Jin, H.Y.[Hai-Yan],
Yang, X.H.[Xiao-Hui],
Jiao, L.C.[Li-Cheng],
Liu, F.[Fang],
Image Enhancement via Fusion Based on Laplacian Pyramid Directional
Filter Banks,
ICIAR05(239-246).
Springer DOI
0509
BibRef
Omrane, N.,
Palmer, P.,
Super-resolution using the Walsh functions, a new algorithm for image
reconstruction,
ICIP03(II: 299-302).
IEEE DOI
0312
BibRef
Kim, H.,
Jang, J.H.,
Hong, K.S.,
Edge-enhancing Super-resolution Using Anisotropic Diffusion,
ICIP01(III: 130-133).
IEEE DOI
0108
BibRef
Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Stereo Image Super Resolution .