Multiscale and Multitopic Sparse Representation for Multisensor Infrared Image Superresolution
Methods based on sparse coding have been successfully used in single-image superresolution (SR) reconstruction. However, the traditional sparse representation-based SR image reconstruction for infrared (IR) images usually suffers from three problems. First, IR images always lack detailed information...
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| Veröffentlicht in: | Journal of sensors Jg. 2016; H. 2016; S. 1 - 14 |
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| Hauptverfasser: | , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
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Cairo, Egypt
Hindawi Publishing Corporation
01.01.2016
John Wiley & Sons, Inc |
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| ISSN: | 1687-725X, 1687-7268 |
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| Abstract | Methods based on sparse coding have been successfully used in single-image superresolution (SR) reconstruction. However, the traditional sparse representation-based SR image reconstruction for infrared (IR) images usually suffers from three problems. First, IR images always lack detailed information. Second, a traditional sparse dictionary is learned from patches with a fixed size, which may not capture the exact information of the images and may ignore the fact that images naturally come at different scales in many cases. Finally, traditional sparse dictionary learning methods aim at learning a universal and overcomplete dictionary. However, many different local structural patterns exist. One dictionary is inadequate in capturing all of the different structures. We propose a novel IR image SR method to overcome these problems. First, we combine the information from multisensors to improve the resolution of the IR image. Then, we use multiscale patches to represent the image in a more efficient manner. Finally, we partition the natural images into documents and group such documents to determine the inherent topics and to learn the sparse dictionary of each topic. Extensive experiments validate that using the proposed method yields better results in terms of quantitation and visual perception than many state-of-the-art algorithms. |
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| AbstractList | Methods based on sparse coding have been successfully used in single-image superresolution (SR) reconstruction. However, the traditional sparse representation-based SR image reconstruction for infrared (IR) images usually suffers from three problems. First, IR images always lack detailed information. Second, a traditional sparse dictionary is learned from patches with a fixed size, which may not capture the exact information of the images and may ignore the fact that images naturally come at different scales in many cases. Finally, traditional sparse dictionary learning methods aim at learning a universal and overcomplete dictionary. However, many different local structural patterns exist. One dictionary is inadequate in capturing all of the different structures. We propose a novel IR image SR method to overcome these problems. First, we combine the information from multisensors to improve the resolution of the IR image. Then, we use multiscale patches to represent the image in a more efficient manner. Finally, we partition the natural images into documents and group such documents to determine the inherent topics and to learn the sparse dictionary of each topic. Extensive experiments validate that using the proposed method yields better results in terms of quantitation and visual perception than many state-of-the-art algorithms. |
| Author | Yan, Binyu Liu, Kai Yang, Xiaomin Gan, Zhongliang |
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| Cites_doi | 10.1007/978-3-642-37431-9_22 10.1137/070697653 10.1002/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9 10.1109/tip.2010.2050625 10.1023/a:1007617005950 10.1016/j.optcom.2012.08.101 10.1109/TIP.2004.840683 10.1109/38.988747 10.1109/tip.2012.2208977 10.1109/83.784434 10.1109/JPROC.2010.2040551 10.1016/j.imavis.2011.02.001 10.1016/j.sigpro.2009.09.002 10.1109/tip.2006.888334 10.1109/TIP.2004.834669 10.1109/tsmcc.2005.848171 10.1007/978-3-642-27413-8_47 10.1109/jstsp.2010.2048606 10.1109/TSP.2006.881199 |
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| Copyright | Copyright © 2016 Xiaomin Yang et al. Copyright © 2016 Xiaomin Yang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
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| DOI | 10.1155/2016/7036349 |
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| References | (9) 2005; 35 Sun J. Sun J. Xu Z. Shum H.-Y. Image super-resolution using gradient profile prior Proceedings of the 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR '08) June 2008 1 8 10.1109/cvpr.2008.4587659 2-s2.0-51949110386 Mairal J. Bach F. Ponce J. Sapiro G. Zisserman A. Supervised dictionary learning Proceedings of the 22nd Annual Conference on Neural Information Processing Systems (NIPS '08) December 2008 1033 1040 2-s2.0-84858761801 Monaci G. Vanderqheynst P. Learning structured dictionaries for image representation 4 Proceedings of the IEEE International Conference on Image Processing (ICIP '04) October 2004 Singapore IEEE 2351 2354 10.1109/ICIP.2004.1421572 (1) 1999; 8 (17) 2010; 98 (6) 2004; 13 (2) 2005; 14 (4) 2007; 16 (16) 2010; 19 (21) 2013; 287 Purkait P. Chanda B. Image upscaling using multiple dictionaries of natural image patches Computer Vision—ACCV 2012: 11th Asian Conference on Computer Vision, Daejeon, Korea, November 5–9, 2012, Revised Selected Papers, Part III 2013 7726 Berlin, Germany Springer 284 295 Lecture Notes in Computer Science 10.1007/978-3-642-37431-9_22 (13) 2008; 7 Chang H. Yeung D.-Y. Xiong Y. Super-resolution through neighbor embedding 1 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR ’04) June-July 2004 Washington, DC, USA 275 282 10.1109/CVPR.2004.1315043 (23) 1990; 41 Morris N. J. W. Avidan S. Matusik W. Pfister H. Statistics of infrared images Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR' 07) June 2007 1 7 10.1109/cvpr.2007.383003 2-s2.0-35148848710 (5) 2010; 90 Zeyde R. Elad M. Protter M. On single image scale-up using sparse-representations Curves and Surfaces 2012 6920 711 730 Lecture Notes in Computer Science 10.1007/978-3-642-27413-8_47 (7) 2002; 22 (11) 2006; 54 (10) 2011; 29 (18) 2012; 21 (3) 1984; 1 (8) 2011; 5 (19) 2001; 42 11 22 23 13 14 25 15 26 16 27 17 28 18 1 2 8 9 10 21 |
| References_xml | – volume: 8 start-page: 1221 issue: 9 year: 1999 end-page: 1228 ident: 1 article-title: Demosaicing: image reconstruction from color CCD samples – volume: 16 start-page: 479 issue: 2 year: 2007 end-page: 490 ident: 4 article-title: A MAP approach for joint motion estimation, segmentation, and super resolution – volume: 90 start-page: 848 issue: 3 year: 2010 end-page: 859 ident: 5 article-title: A super-resolution reconstruction algorithm for surveillance images – volume: 54 start-page: 4311 issue: 11 year: 2006 end-page: 4322 ident: 11 article-title: K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation – reference: Zeyde R. Elad M. Protter M. On single image scale-up using sparse-representations Curves and Surfaces 2012 6920 711 730 Lecture Notes in Computer Science 10.1007/978-3-642-27413-8_47 – volume: 5 start-page: 230 issue: 2 year: 2011 end-page: 239 ident: 8 article-title: Partially supervised neighbor embedding for example-based image super-resolution – reference: Purkait P. Chanda B. Image upscaling using multiple dictionaries of natural image patches Computer Vision—ACCV 2012: 11th Asian Conference on Computer Vision, Daejeon, Korea, November 5–9, 2012, Revised Selected Papers, Part III 2013 7726 Berlin, Germany Springer 284 295 Lecture Notes in Computer Science 10.1007/978-3-642-37431-9_22 – volume: 19 start-page: 2861 issue: 11 year: 2010 end-page: 2873 ident: 16 article-title: Image super-resolution via sparse representation – reference: Sun J. Sun J. Xu Z. Shum H.-Y. Image super-resolution using gradient profile prior Proceedings of the 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR '08) June 2008 1 8 10.1109/cvpr.2008.4587659 2-s2.0-51949110386 – reference: Mairal J. Bach F. Ponce J. Sapiro G. Zisserman A. Supervised dictionary learning Proceedings of the 22nd Annual Conference on Neural Information Processing Systems (NIPS '08) December 2008 1033 1040 2-s2.0-84858761801 – volume: 13 start-page: 1327 issue: 10 year: 2004 end-page: 1344 ident: 6 article-title: Fast and robust multiframe super resolution – reference: Chang H. Yeung D.-Y. Xiong Y. Super-resolution through neighbor embedding 1 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR ’04) June-July 2004 Washington, DC, USA 275 282 10.1109/CVPR.2004.1315043 – volume: 98 start-page: 1045 issue: 6 year: 2010 end-page: 1057 ident: 17 article-title: Dictionaries for sparse representation modeling – volume: 1 start-page: 317 year: 1984 end-page: 339 ident: 3 article-title: Multi-frame image restoration and registration – reference: Monaci G. Vanderqheynst P. Learning structured dictionaries for image representation 4 Proceedings of the IEEE International Conference on Image Processing (ICIP '04) October 2004 Singapore IEEE 2351 2354 10.1109/ICIP.2004.1421572 – volume: 41 start-page: 391 issue: 6 year: 1990 end-page: 407 ident: 23 article-title: Indexing by latent semantic analysis – volume: 42 start-page: 177 issue: 1-2 year: 2001 end-page: 196 ident: 19 article-title: Unsupervised learning by probabilistic latent semantic analysis – reference: Morris N. J. W. Avidan S. Matusik W. Pfister H. Statistics of infrared images Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR' 07) June 2007 1 7 10.1109/cvpr.2007.383003 2-s2.0-35148848710 – volume: 35 start-page: 425 issue: 3 year: 2005 end-page: 434 ident: 9 article-title: Hallucinating face by eigentransformation – volume: 29 start-page: 394 issue: 6 year: 2011 end-page: 406 ident: 10 article-title: Learning-based super resolution using kernel partial least squares – volume: 22 start-page: 56 issue: 2 year: 2002 end-page: 65 ident: 7 article-title: Example-based super-resolution – volume: 7 start-page: 214 issue: 1 year: 2008 end-page: 241 ident: 13 article-title: Learning multiscale sparse representations for image and video restoration – volume: 287 start-page: 63 issue: 1 year: 2013 end-page: 72 ident: 21 article-title: A multifocus image fusion method by using hidden Markov model – volume: 21 start-page: 4544 issue: 11 year: 2012 end-page: 4556 ident: 18 article-title: Single image super-resolution with non-local means and steering kernel regression – volume: 14 start-page: 370 issue: 3 year: 2005 end-page: 379 ident: 2 article-title: Demosaicing by successive approximation – ident: 28 doi: 10.1007/978-3-642-37431-9_22 – ident: 18 doi: 10.1137/070697653 – ident: 27 doi: 10.1002/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9 – ident: 16 doi: 10.1109/tip.2010.2050625 – ident: 26 doi: 10.1023/a:1007617005950 – ident: 25 doi: 10.1016/j.optcom.2012.08.101 – ident: 2 doi: 10.1109/TIP.2004.840683 – ident: 11 doi: 10.1109/38.988747 – ident: 23 doi: 10.1109/tip.2012.2208977 – ident: 1 doi: 10.1109/83.784434 – ident: 21 doi: 10.1109/JPROC.2010.2040551 – ident: 15 doi: 10.1016/j.imavis.2011.02.001 – ident: 9 doi: 10.1016/j.sigpro.2009.09.002 – volume: 1 start-page: 317 year: 1984 ident: 3 publication-title: Advances in Computer Vision and Image Processing – ident: 8 doi: 10.1109/tip.2006.888334 – ident: 10 doi: 10.1109/TIP.2004.834669 – ident: 14 doi: 10.1109/tsmcc.2005.848171 – ident: 22 doi: 10.1007/978-3-642-27413-8_47 – ident: 13 doi: 10.1109/jstsp.2010.2048606 – ident: 17 doi: 10.1109/TSP.2006.881199 |
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| SubjectTerms | Algorithms Dictionaries Image reconstruction Infrared Learning Representations State of the art |
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| Title | Multiscale and Multitopic Sparse Representation for Multisensor Infrared Image Superresolution |
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