Sparse coding with morphology segmentation and multi-label fusion for hyperspectral image super-resolution
Hyperspectral image (HSI) super-solution to reconstruct high spatial resolution HSIs has attracted increasing interest in recent years. In this paper, we propose a HSI super-resolution framework based on sparse coding with morphology segmentation and multi-label fusion (MSML), which is composed of f...
Saved in:
| Published in | Computer vision and image understanding Vol. 227; p. 103603 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Inc
01.01.2023
|
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | Hyperspectral image (HSI) super-solution to reconstruct high spatial resolution HSIs has attracted increasing interest in recent years. In this paper, we propose a HSI super-resolution framework based on sparse coding with morphology segmentation and multi-label fusion (MSML), which is composed of four stages: (1) A spectral dictionary is learned by the online dictionary learning approach from the given HSI; (2) The morphology segmentation technique is introduced to divide each multispectral image (MSI) band into a series of regions associated with a label map; (3) A weighted voting based multi-label fusion model is constructed to combine multiple label maps from MSI bands to determine 3-D patches; (4) A sparse coding model is built to calculate sparse coefficients of 3-D patches that are used for the HSI super-solution. Compared with traditional sparse representation based algorithms, the novel MSML method can more fully utilize the local spatial information of the MSI to realize the super-resolution, relying on the sparse coding on unfixed-size patches adaptively obtained by the morphology segmentation and multi-label fusion. The Indian Pines, Salinas, Botswana, and Pavia University datasets are used to evaluate the performance of our method. Experimental results indicate that the MSML achieves better super-resolution performance in contrast to state-of-the-art algorithms.
•Morphology segmentation is used to get unfixed-size 2-D patches of each MSI band.•Weighted voting based multi-label fusion is built to get unfixed-size 3-D patches.•Patch-wise sparse representation model is formed on the 3-D patches. |
|---|---|
| AbstractList | Hyperspectral image (HSI) super-solution to reconstruct high spatial resolution HSIs has attracted increasing interest in recent years. In this paper, we propose a HSI super-resolution framework based on sparse coding with morphology segmentation and multi-label fusion (MSML), which is composed of four stages: (1) A spectral dictionary is learned by the online dictionary learning approach from the given HSI; (2) The morphology segmentation technique is introduced to divide each multispectral image (MSI) band into a series of regions associated with a label map; (3) A weighted voting based multi-label fusion model is constructed to combine multiple label maps from MSI bands to determine 3-D patches; (4) A sparse coding model is built to calculate sparse coefficients of 3-D patches that are used for the HSI super-solution. Compared with traditional sparse representation based algorithms, the novel MSML method can more fully utilize the local spatial information of the MSI to realize the super-resolution, relying on the sparse coding on unfixed-size patches adaptively obtained by the morphology segmentation and multi-label fusion. The Indian Pines, Salinas, Botswana, and Pavia University datasets are used to evaluate the performance of our method. Experimental results indicate that the MSML achieves better super-resolution performance in contrast to state-of-the-art algorithms.
•Morphology segmentation is used to get unfixed-size 2-D patches of each MSI band.•Weighted voting based multi-label fusion is built to get unfixed-size 3-D patches.•Patch-wise sparse representation model is formed on the 3-D patches. |
| ArticleNumber | 103603 |
| Author | Xing, Changda Liu, Yiliu Cong, Yuhua Wang, Zhisheng Wang, Meiling Duan, Chaowei |
| Author_xml | – sequence: 1 givenname: Changda orcidid: 0000-0002-0387-4497 surname: Xing fullname: Xing, Changda organization: College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China – sequence: 2 givenname: Meiling orcidid: 0000-0001-6569-2798 surname: Wang fullname: Wang, Meiling email: mely@nuaa.edu.cn organization: College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China – sequence: 3 givenname: Yuhua surname: Cong fullname: Cong, Yuhua organization: College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China – sequence: 4 givenname: Zhisheng surname: Wang fullname: Wang, Zhisheng organization: College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China – sequence: 5 givenname: Chaowei orcidid: 0000-0001-8958-1822 surname: Duan fullname: Duan, Chaowei organization: College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China – sequence: 6 givenname: Yiliu surname: Liu fullname: Liu, Yiliu organization: College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China |
| BookMark | eNp9kMtKxDAUhoMoODP6Aq7yAh1z6RXcyOANBlyo4C6kyUknpU1K0o7M29syrl2dww_f4T_fGl067wChO0q2lND8vt2qo522jDA2Bzwn_AKtKKlIwnj2fbnsRZFwmrJrtI6xJYTStKIr1H4MMkTAymvrGvxjxwPufRgOvvPNCUdoenCjHK13WDqN-6kbbdLJGjpsprjExgd8OA0Q4gBqDLLDtpcN4DjNWRIg-m5a-Bt0ZWQX4fZvbtDX89Pn7jXZv7-87R73ieKEjInSNU0L0KzkWsvMlCVQrXkBqTaK85JzWlGVqbQEWatK55nOpamrVLJMq7riG8TOd1XwMQYwYghzo3ASlIjFlmjFYksstsTZ1gw9nCGYmx0tBBGVBadA2zB_JbS3_-G_Yx55dA |
| CitedBy_id | crossref_primary_10_1016_j_cviu_2023_103765 |
| Cites_doi | 10.1109/ICCV.2015.409 10.1109/MGRS.2016.2637824 10.1109/TGRS.2010.2068053 10.1109/TGRS.2014.2318058 10.1109/TGRS.2007.904923 10.1109/TGRS.2018.2797200 10.1109/LGRS.2012.2193372 10.1109/TNNLS.2020.2980398 10.3390/rs9050443 10.1145/1553374.1553463 10.1109/TIP.2020.3044214 10.1109/TGRS.2013.2253612 10.1109/34.87344 10.1016/j.sigpro.2020.107585 10.1109/TGRS.2014.2367129 10.1007/978-3-319-10584-0_5 10.1109/TGRS.2007.901007 10.1109/97.995823 10.7551/mitpress/7503.003.0105 10.1109/TIP.2015.2496263 10.1109/TMI.2019.2899910 10.1109/ATSIP.2014.6834602 10.1109/TCI.2020.2996075 10.1109/JSTSP.2015.2423260 10.1109/TIP.2015.2458572 10.1109/TIP.2016.2545248 10.1109/TGRS.2021.3085672 10.1016/j.neucom.2020.04.002 10.1109/TGRS.2014.2375320 10.1109/MGRS.2015.2440094 10.1016/j.isprsjprs.2018.05.014 10.1016/j.sigpro.2005.05.030 10.1137/07070156X 10.1016/j.neucom.2017.08.019 10.1007/978-3-030-58526-6_13 10.1109/TGRS.2017.2713123 10.1109/TIP.2016.2542360 10.1109/TGRS.2016.2598784 10.1109/TGRS.2011.2161320 10.1016/j.inffus.2013.08.005 10.1109/TCSVT.2021.3078559 10.1109/TGRS.2014.2381272 10.1109/TGRS.2018.2815044 10.1109/TIP.2018.2836307 10.1109/IGARSS.2014.6947018 10.1109/TMI.2017.2737081 10.1109/CVPR.2017.411 |
| ContentType | Journal Article |
| Copyright | 2022 Elsevier Inc. |
| Copyright_xml | – notice: 2022 Elsevier Inc. |
| DBID | AAYXX CITATION |
| DOI | 10.1016/j.cviu.2022.103603 |
| DatabaseName | CrossRef |
| DatabaseTitle | CrossRef |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Applied Sciences Engineering Computer Science |
| EISSN | 1090-235X |
| ExternalDocumentID | 10_1016_j_cviu_2022_103603 S1077314222001813 |
| GroupedDBID | --K --M -~X .DC .~1 0R~ 1B1 1~. 1~5 29F 4.4 457 4G. 5GY 5VS 6TJ 7-5 71M 8P~ AABNK AACTN AAEDT AAEDW AAIAV AAIKC AAIKJ AAKOC AALRI AAMNW AAOAW AAQFI AAQXK AAXUO AAYFN ABBOA ABEFU ABFNM ABJNI ABMAC ABXDB ABYKQ ACDAQ ACGFS ACNNM ACRLP ACZNC ADBBV ADEZE ADFGL ADJOM ADMUD ADTZH AEBSH AECPX AEKER AENEX AFKWA AFTJW AGHFR AGUBO AGYEJ AHJVU AHZHX AIALX AIEXJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD ASPBG AVWKF AXJTR AZFZN BJAXD BKOJK BLXMC CAG COF CS3 DM4 DU5 EBS EFBJH EFLBG EJD EO8 EO9 EP2 EP3 F0J F5P FDB FEDTE FGOYB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ HF~ HVGLF HZ~ IHE J1W JJJVA KOM LG5 M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RIG RNS ROL RPZ SDF SDG SDP SES SEW SPC SPCBC SSV SSZ T5K TN5 XPP ZMT ~G- AAXKI AAYXX AFJKZ AKRWK CITATION SST |
| ID | FETCH-LOGICAL-c300t-cdb147ed283dda5f88e1dd37e4dfc33833191c5c48eabc9d65d6afb94a25dcb93 |
| IEDL.DBID | AIKHN |
| ISSN | 1077-3142 |
| IngestDate | Thu Sep 26 17:16:16 EDT 2024 Fri Feb 23 02:39:29 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Hyperspectral image super-resolution Sparse coding Morphology segmentation Multi-label fusion |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c300t-cdb147ed283dda5f88e1dd37e4dfc33833191c5c48eabc9d65d6afb94a25dcb93 |
| ORCID | 0000-0002-0387-4497 0000-0001-6569-2798 0000-0001-8958-1822 |
| ParticipantIDs | crossref_primary_10_1016_j_cviu_2022_103603 elsevier_sciencedirect_doi_10_1016_j_cviu_2022_103603 |
| PublicationCentury | 2000 |
| PublicationDate | January 2023 2023-01-00 |
| PublicationDateYYYYMMDD | 2023-01-01 |
| PublicationDate_xml | – month: 01 year: 2023 text: January 2023 |
| PublicationDecade | 2020 |
| PublicationTitle | Computer vision and image understanding |
| PublicationYear | 2023 |
| Publisher | Elsevier Inc |
| Publisher_xml | – name: Elsevier Inc |
| References | Loncan, Almeida, Bioucasdias, Briottet, Chanussot, Dobigeon, Fabre, Liao, Licciardi, Simes (b22) 2015; 3 Huang, Song, Cui, Peng, Xu (b16) 2014; 52 Wang, Bovik (b31) 2002; 9 Xing, Wang, Wang, Duan, Liu (b40) 2022; 60 Vivone, G., Restaino, R., Licciardi, G.A., Mura, M.D., Chanussot, J., 2014. MultiResolution Analysis and Component Substitution techniques for hyperspectral Pansharpening. In: IEEE International Geoscience and Remote Sensing Symposium. pp. 2649–2652. Gaetano, Masi, Poggi, Verdoliva, Scarpa (b14) 2015; 53 Mairal, J., Bach, F., Ponce, J., Sapiro, G., 2009. Online dictionary learning for sparse coding. In: IEEE International Conference on Machine Learning. pp. 689–696. Aiazzi, Baronti, Selva (b2) 2007; 45 Tropp, Gilbert, Strauss (b27) 2006; 86 Hallabia, H., Kallel, A., Hamida, A.B., 2014. Image pansharpening: Comparison of methods based on multiresolution analysis and component substitution. In: IEEE International Conference on Advanced Technologies for Signal and Image Processing. pp. 25–30. Alparone, Wald, Chanussot, Thomas, Gamba, Bruce (b5) 2007; 45 Song, Huang, Zhang, Zhang (b26) 2014; 18 Yokoya, Yairi, Iwasaki (b45) 2012; 50 Wei, Bioucas-Dias, Dobigeon, Tourneret, Chen, Godsill (b35) 2016; 50 Aharon, Elad (b1) 2008; 1 Dong, Fu, Shi, Cao, Wu, Li, Li (b9) 2016; 25 Fang, Zhuo, Li (b13) 2018; 273 Wei, Dobigeon, Tourneret (b36) 2015; 24 Fang, Li, Kang, Benediktsson (b12) 2014; 52 Fan, Clausi, Xu, Wong (b11) 2018; 56 Beucher (b6) 1994 Wei, Bioucas-Dias, Dobigeon, Tourneret (b34) 2015; 53 Xing, Wang, Duan, Wang (b39) 2020; 402 Dian, R., Fang, L., Li, S., 2017. Hyperspectral Image Super-Resolution via Non-local Sparse Tensor Factorization. In: IEEE International Conference on Computer Vision and Pattern Recognition. pp. 3862–3871. Zhang, Li, Li, Deng, Plaza (b46) 2018; 56 Lanaras, C., Baltsavias, E., Schindler, K., 2015. Hyperspectral Super-Resolution by Coupled Spectral Unmixing. In: IEEE International Conference on Computer Vision. pp. 3586–3594. Wang, Yu, Yang, Fu, Heng (b33) 2019; 38 Alansary, Rajchl, Mcdonagh, Murgasova, Damodaram, Dfa, Davidson, Rutherford, Hajnal, Rueckert (b4) 2017; 36 Zhu, Hou, Chen, Zeng, Zhou (b49) 2021; 30 Du, Xue, Li, Plaza (b10) 2017; 9 Yokoya, Grohnfeldt, Chanussot (b44) 2017; 5 Liu, Wei, Wang, Zhang (b21) 2011; 49 Veganzones, Simoes, Licciardi, Yokoya, Bioucas-Dias, Chanussot (b28) 2015; 25 Xie, Zhang, Huang (b37) 2017; 9 Dian, Li, Kang (b8) 2021; 32 Lee, H., Battle, A., Raina, R., Ng, A.Y., 2007. Efficient sparse coding algorithms. In: Conference and Workshop on Neural Information Processing Systems. pp. 801–808. Renza, Martinez, Arquero (b24) 2013; 10 Yang, Shi (b42) 2016; 25 Yao, J., Hong, D., Chanussot, J., Meng, D., Zhu, X., Xu, Z., 2020. Cross-Attention in Coupled Unmixing Nets for Unsupervised Hyperspectral Super-Resolution. In: European Conference on Computer Vision. pp. 208–224. Zhang, L., Yang, M., Feng, X., 2012. Sparse Representation or Collaborative Representation: Which Helps Face Recognition?. In: IEEE International Conference on Computer Vision. pp. 6–13. Zhang, Zhang, Li, Cheng, Jiao, Zhou (b48) 2018; 56 Jiang, Sun, Liu, Ma (b17) 2020; 6 Simes, Bioucas-Dias, Almeida, Chanussot (b25) 2015; 53 Vincent, Soille (b29) 1991; 13 Wang, Chen, Wei, Richard (b32) 2022; 32 Akhtar, N., Shafait, F., Mian, A., 2014. Sparse Spatio-spectral Representation for Hyperspectral Image Super-resolution. In: European Conference on Computer Vision. pp. 63–78. Xu, Du, Zhang (b41) 2018; 142 Li, Dian, Fang, Bioucas-Dias (b20) 2018; 27 Xing, Wang, Dong, Duan, Wang (b38) 2020; 173 Gaetano (10.1016/j.cviu.2022.103603_b14) 2015; 53 Simes (10.1016/j.cviu.2022.103603_b25) 2015; 53 Aiazzi (10.1016/j.cviu.2022.103603_b2) 2007; 45 Fang (10.1016/j.cviu.2022.103603_b12) 2014; 52 Yang (10.1016/j.cviu.2022.103603_b42) 2016; 25 Tropp (10.1016/j.cviu.2022.103603_b27) 2006; 86 Xu (10.1016/j.cviu.2022.103603_b41) 2018; 142 Huang (10.1016/j.cviu.2022.103603_b16) 2014; 52 Wei (10.1016/j.cviu.2022.103603_b34) 2015; 53 Zhang (10.1016/j.cviu.2022.103603_b46) 2018; 56 10.1016/j.cviu.2022.103603_b23 Wang (10.1016/j.cviu.2022.103603_b31) 2002; 9 Song (10.1016/j.cviu.2022.103603_b26) 2014; 18 Fan (10.1016/j.cviu.2022.103603_b11) 2018; 56 10.1016/j.cviu.2022.103603_b19 10.1016/j.cviu.2022.103603_b18 Zhang (10.1016/j.cviu.2022.103603_b48) 2018; 56 Alparone (10.1016/j.cviu.2022.103603_b5) 2007; 45 Dong (10.1016/j.cviu.2022.103603_b9) 2016; 25 Jiang (10.1016/j.cviu.2022.103603_b17) 2020; 6 Renza (10.1016/j.cviu.2022.103603_b24) 2013; 10 Aharon (10.1016/j.cviu.2022.103603_b1) 2008; 1 10.1016/j.cviu.2022.103603_b15 Li (10.1016/j.cviu.2022.103603_b20) 2018; 27 Loncan (10.1016/j.cviu.2022.103603_b22) 2015; 3 Alansary (10.1016/j.cviu.2022.103603_b4) 2017; 36 Yokoya (10.1016/j.cviu.2022.103603_b44) 2017; 5 Fang (10.1016/j.cviu.2022.103603_b13) 2018; 273 Wei (10.1016/j.cviu.2022.103603_b36) 2015; 24 Zhu (10.1016/j.cviu.2022.103603_b49) 2021; 30 Xing (10.1016/j.cviu.2022.103603_b40) 2022; 60 Du (10.1016/j.cviu.2022.103603_b10) 2017; 9 Wang (10.1016/j.cviu.2022.103603_b33) 2019; 38 Wang (10.1016/j.cviu.2022.103603_b32) 2022; 32 Wei (10.1016/j.cviu.2022.103603_b35) 2016; 50 10.1016/j.cviu.2022.103603_b47 10.1016/j.cviu.2022.103603_b43 Yokoya (10.1016/j.cviu.2022.103603_b45) 2012; 50 Xing (10.1016/j.cviu.2022.103603_b38) 2020; 173 Liu (10.1016/j.cviu.2022.103603_b21) 2011; 49 Dian (10.1016/j.cviu.2022.103603_b8) 2021; 32 Xie (10.1016/j.cviu.2022.103603_b37) 2017; 9 10.1016/j.cviu.2022.103603_b30 10.1016/j.cviu.2022.103603_b3 Veganzones (10.1016/j.cviu.2022.103603_b28) 2015; 25 Beucher (10.1016/j.cviu.2022.103603_b6) 1994 10.1016/j.cviu.2022.103603_b7 Xing (10.1016/j.cviu.2022.103603_b39) 2020; 402 Vincent (10.1016/j.cviu.2022.103603_b29) 1991; 13 |
| References_xml | – start-page: 69 year: 1994 end-page: 76 ident: b6 article-title: Watershed, hierarchical segmentation and waterfall algorithm publication-title: Mathematical Morphology and Its Applications to Signal Processing contributor: fullname: Beucher – volume: 45 start-page: 3230 year: 2007 end-page: 3239 ident: b2 article-title: Improving component substitution pansharpening through multivariate regression of MS publication-title: IEEE Trans. Geosci. Remote Sens. contributor: fullname: Selva – volume: 49 start-page: 757 year: 2011 end-page: 772 ident: b21 article-title: An approach based on constrained nonnegative matrix factorization to unmix hyperspectral data publication-title: IEEE Trans. Geosci. Remote Sens. contributor: fullname: Zhang – volume: 9 start-page: 443 year: 2017 ident: b37 article-title: Revealing implicit assumptions of the component substitution pansharpening methods publication-title: Remote Sens. contributor: fullname: Huang – volume: 10 start-page: 76 year: 2013 end-page: 80 ident: b24 article-title: A new approach to change detection in multispectral images by means of ERGAS index publication-title: IEEE Geosci. Remote Sens. Lett. contributor: fullname: Arquero – volume: 53 start-page: 3373 year: 2015 end-page: 3388 ident: b25 article-title: A convex formulation for hyperspectral image superresolution via subspace-based regularization publication-title: IEEE Trans. Geosci. Remote Sens. contributor: fullname: Chanussot – volume: 9 start-page: 81 year: 2002 end-page: 84 ident: b31 article-title: A universal image quality index publication-title: Signal Process. Lett. contributor: fullname: Bovik – volume: 53 start-page: 2987 year: 2015 end-page: 3004 ident: b14 article-title: Marker-controlled watershed-based segmentation of multiresolution remote sensing images publication-title: IEEE Trans. Geosci. Remote Sens. contributor: fullname: Scarpa – volume: 25 start-page: 2337 year: 2016 end-page: 2352 ident: b9 article-title: Hyperspectral image super-resolution via non-negative structured sparse representation publication-title: IEEE Trans. Image Process. contributor: fullname: Li – volume: 25 start-page: 274 year: 2015 end-page: 288 ident: b28 article-title: Hyperspectral super-resolution of locally low rank images from complementary multisource data publication-title: IEEE Trans. Image Process. contributor: fullname: Chanussot – volume: 18 start-page: 148 year: 2014 end-page: 160 ident: b26 article-title: Spatio-spectral fusion of satellite images based on dictionary-pair learning publication-title: Inf. Fusion contributor: fullname: Zhang – volume: 50 start-page: 528 year: 2012 end-page: 537 ident: b45 article-title: Coupled nonnegative matrix factorization unmixing for hyperspectral and multispectral data fusion publication-title: IEEE Trans. Geosci. Remote Sens. contributor: fullname: Iwasaki – volume: 56 start-page: 3265 year: 2018 end-page: 3276 ident: b46 article-title: Spectral-spatial weighted sparse regression for hyperspectral image unmixing publication-title: IEEE Trans. Geosci. Remote Sens. contributor: fullname: Plaza – volume: 32 start-page: 1124 year: 2021 end-page: 1135 ident: b8 article-title: Regularizing hyperspectral and multispectral image fusion by CNN denoiser publication-title: IEEE Trans. Neural Netw. Learn. Syst. contributor: fullname: Kang – volume: 56 start-page: 3 year: 2018 end-page: 16 ident: b11 article-title: ST-IRGS: A region-based self-training algorithm applied to hyperspectral image classification and segmentation publication-title: IEEE Trans. Geosci. Remote Sens. contributor: fullname: Wong – volume: 5 start-page: 29 year: 2017 end-page: 56 ident: b44 article-title: Hyperspectral and multispectral data fusion: A comparative review publication-title: IEEE Geosci. Remote Sens. Mag. contributor: fullname: Chanussot – volume: 30 start-page: 1423 year: 2021 end-page: 1438 ident: b49 article-title: Hyperspectral image super-resolution via deep progressive zero-centric residual learning publication-title: IEEE Trans. Image Process. contributor: fullname: Zhou – volume: 13 start-page: 589 year: 1991 end-page: 598 ident: b29 article-title: Watersheds in digital spaces: An efficient algorithm based on immersion simulations publication-title: IEEE Trans. Pattern Anal. Mach. Intell. contributor: fullname: Soille – volume: 1 start-page: 228 year: 2008 end-page: 247 ident: b1 article-title: Sparse and redundant modeling of image content using an image-signature-dictionary publication-title: SIAM J. Imaging Sci. contributor: fullname: Elad – volume: 27 start-page: 4118 year: 2018 end-page: 4130 ident: b20 article-title: Fusing hyperspectral and multispectral images via coupled sparse tensor factorization publication-title: IEEE Trans. Image Process. contributor: fullname: Bioucas-Dias – volume: 36 start-page: 2031 year: 2017 end-page: 2044 ident: b4 article-title: PVR: Patch-to-volume reconstruction for large area motion correction of fetal MRI publication-title: IEEE Trans. Med. Imaging contributor: fullname: Rueckert – volume: 45 start-page: 3012 year: 2007 end-page: 3021 ident: b5 article-title: Comparison of pansharpening algorithms: Outcome of the 2006 GRS-S data fusion contest publication-title: IEEE Trans. Geosci. Remote Sens. contributor: fullname: Bruce – volume: 273 start-page: 171 year: 2018 end-page: 177 ident: b13 article-title: Super-resolution of hyperspectral image via superpixel-based sparse representation publication-title: Neurocomputing contributor: fullname: Li – volume: 173 year: 2020 ident: b38 article-title: Joint sparse-collaborative representation to fuse hyperspectral and multispectral images publication-title: Signal Process. contributor: fullname: Wang – volume: 25 start-page: 2249 year: 2016 end-page: 2258 ident: b42 article-title: Hyperspectral image target detection improvement based on total variation publication-title: IEEE Trans. Image Process. contributor: fullname: Shi – volume: 9 start-page: 1089 year: 2017 end-page: 1104 ident: b10 article-title: Learning discriminative sparse representations for hyperspectral image classification publication-title: IEEE J. Sel. Top. Sign. Proces. contributor: fullname: Plaza – volume: 60 year: 2022 ident: b40 article-title: Diagonalized low-rank learning for hyperspectral image classification publication-title: IEEE Trans. Geosci. Remote Sens. contributor: fullname: Liu – volume: 52 start-page: 7738 year: 2014 end-page: 7749 ident: b12 article-title: Spectral–spatial hyperspectral image classification via multiscale adaptive sparse representation publication-title: IEEE Trans. Geosci. Remote Sens. contributor: fullname: Benediktsson – volume: 38 start-page: 2485 year: 2019 end-page: 2495 ident: b33 article-title: Patch-based output space adversarial learning for joint optic disc and cup segmentation publication-title: IEEE Trans. Med. Imaging contributor: fullname: Heng – volume: 86 start-page: 572 year: 2006 end-page: 588 ident: b27 article-title: Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit publication-title: Signal Process. contributor: fullname: Strauss – volume: 24 start-page: 4109 year: 2015 end-page: 4121 ident: b36 article-title: Fast fusion of multi-band images based on solving a sylvester equation publication-title: IEEE Trans. Image Process. contributor: fullname: Tourneret – volume: 56 start-page: 3861 year: 2018 end-page: 3975 ident: b48 article-title: Hybrid unmixing based on adaptive region segmentation for hyperspectral imagery publication-title: IEEE Trans. Geosci. Remote Sens. contributor: fullname: Zhou – volume: 142 start-page: 344 year: 2018 end-page: 357 ident: b41 article-title: Hyperspectral image classification via a random patches network publication-title: ISPRS J. Photogramm. Remote Sens. contributor: fullname: Zhang – volume: 52 start-page: 1693 year: 2014 end-page: 1704 ident: b16 article-title: Spatial and spectral image fusion using sparse matrix factorization publication-title: IEEE Trans. Geosci. Remote Sens. contributor: fullname: Xu – volume: 402 start-page: 437 year: 2020 end-page: 455 ident: b39 article-title: Using taylor expansion and convolutional sparse representation for image fusion publication-title: Neurocomputing contributor: fullname: Wang – volume: 32 start-page: 1708 year: 2022 end-page: 1723 ident: b32 article-title: Hyperspectral image super-resolution via deep prior regularization with parameter estimation publication-title: IEEE Trans. Circuits Syst. Video Technol. contributor: fullname: Richard – volume: 50 start-page: 7236 year: 2016 end-page: 7249 ident: b35 article-title: Multi-band image fusion based on spectral unmixing publication-title: IEEE Trans. Geosci. Remote Sens. contributor: fullname: Godsill – volume: 3 start-page: 27 year: 2015 end-page: 46 ident: b22 article-title: Hyperspectral pansharpening: a review publication-title: IEEE Geosci. Remote Sens. Mag. contributor: fullname: Simes – volume: 53 start-page: 3658 year: 2015 end-page: 3668 ident: b34 article-title: Hyperspectral and multispectral image fusion based on a sparse representation publication-title: IEEE Trans. Geosci. Remote Sens. contributor: fullname: Tourneret – volume: 6 start-page: 1082 year: 2020 end-page: 1096 ident: b17 article-title: Learning spatial-spectral prior for super-resolution of hyperspectral imagery publication-title: IEEE Trans. Comput. Imaging contributor: fullname: Ma – ident: 10.1016/j.cviu.2022.103603_b18 doi: 10.1109/ICCV.2015.409 – volume: 5 start-page: 29 issue: 2 year: 2017 ident: 10.1016/j.cviu.2022.103603_b44 article-title: Hyperspectral and multispectral data fusion: A comparative review publication-title: IEEE Geosci. Remote Sens. Mag. doi: 10.1109/MGRS.2016.2637824 contributor: fullname: Yokoya – volume: 49 start-page: 757 issue: 2 year: 2011 ident: 10.1016/j.cviu.2022.103603_b21 article-title: An approach based on constrained nonnegative matrix factorization to unmix hyperspectral data publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2010.2068053 contributor: fullname: Liu – volume: 52 start-page: 7738 issue: 12 year: 2014 ident: 10.1016/j.cviu.2022.103603_b12 article-title: Spectral–spatial hyperspectral image classification via multiscale adaptive sparse representation publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2014.2318058 contributor: fullname: Fang – volume: 45 start-page: 3012 issue: 10 year: 2007 ident: 10.1016/j.cviu.2022.103603_b5 article-title: Comparison of pansharpening algorithms: Outcome of the 2006 GRS-S data fusion contest publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2007.904923 contributor: fullname: Alparone – volume: 56 start-page: 3265 issue: 6 year: 2018 ident: 10.1016/j.cviu.2022.103603_b46 article-title: Spectral-spatial weighted sparse regression for hyperspectral image unmixing publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2018.2797200 contributor: fullname: Zhang – volume: 10 start-page: 76 issue: 1 year: 2013 ident: 10.1016/j.cviu.2022.103603_b24 article-title: A new approach to change detection in multispectral images by means of ERGAS index publication-title: IEEE Geosci. Remote Sens. Lett. doi: 10.1109/LGRS.2012.2193372 contributor: fullname: Renza – volume: 32 start-page: 1124 issue: 3 year: 2021 ident: 10.1016/j.cviu.2022.103603_b8 article-title: Regularizing hyperspectral and multispectral image fusion by CNN denoiser publication-title: IEEE Trans. Neural Netw. Learn. Syst. doi: 10.1109/TNNLS.2020.2980398 contributor: fullname: Dian – volume: 9 start-page: 443 issue: 5 year: 2017 ident: 10.1016/j.cviu.2022.103603_b37 article-title: Revealing implicit assumptions of the component substitution pansharpening methods publication-title: Remote Sens. doi: 10.3390/rs9050443 contributor: fullname: Xie – ident: 10.1016/j.cviu.2022.103603_b23 doi: 10.1145/1553374.1553463 – volume: 30 start-page: 1423 year: 2021 ident: 10.1016/j.cviu.2022.103603_b49 article-title: Hyperspectral image super-resolution via deep progressive zero-centric residual learning publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2020.3044214 contributor: fullname: Zhu – volume: 52 start-page: 1693 issue: 3 year: 2014 ident: 10.1016/j.cviu.2022.103603_b16 article-title: Spatial and spectral image fusion using sparse matrix factorization publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2013.2253612 contributor: fullname: Huang – volume: 13 start-page: 589 issue: 6 year: 1991 ident: 10.1016/j.cviu.2022.103603_b29 article-title: Watersheds in digital spaces: An efficient algorithm based on immersion simulations publication-title: IEEE Trans. Pattern Anal. Mach. Intell. doi: 10.1109/34.87344 contributor: fullname: Vincent – volume: 173 year: 2020 ident: 10.1016/j.cviu.2022.103603_b38 article-title: Joint sparse-collaborative representation to fuse hyperspectral and multispectral images publication-title: Signal Process. doi: 10.1016/j.sigpro.2020.107585 contributor: fullname: Xing – volume: 53 start-page: 2987 issue: 6 year: 2015 ident: 10.1016/j.cviu.2022.103603_b14 article-title: Marker-controlled watershed-based segmentation of multiresolution remote sensing images publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2014.2367129 contributor: fullname: Gaetano – ident: 10.1016/j.cviu.2022.103603_b3 doi: 10.1007/978-3-319-10584-0_5 – volume: 45 start-page: 3230 issue: 10 year: 2007 ident: 10.1016/j.cviu.2022.103603_b2 article-title: Improving component substitution pansharpening through multivariate regression of MS +pan data publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2007.901007 contributor: fullname: Aiazzi – volume: 9 start-page: 81 issue: 3 year: 2002 ident: 10.1016/j.cviu.2022.103603_b31 article-title: A universal image quality index publication-title: Signal Process. Lett. doi: 10.1109/97.995823 contributor: fullname: Wang – ident: 10.1016/j.cviu.2022.103603_b19 doi: 10.7551/mitpress/7503.003.0105 – volume: 25 start-page: 274 issue: 1 year: 2015 ident: 10.1016/j.cviu.2022.103603_b28 article-title: Hyperspectral super-resolution of locally low rank images from complementary multisource data publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2015.2496263 contributor: fullname: Veganzones – volume: 38 start-page: 2485 issue: 11 year: 2019 ident: 10.1016/j.cviu.2022.103603_b33 article-title: Patch-based output space adversarial learning for joint optic disc and cup segmentation publication-title: IEEE Trans. Med. Imaging doi: 10.1109/TMI.2019.2899910 contributor: fullname: Wang – ident: 10.1016/j.cviu.2022.103603_b15 doi: 10.1109/ATSIP.2014.6834602 – volume: 6 start-page: 1082 year: 2020 ident: 10.1016/j.cviu.2022.103603_b17 article-title: Learning spatial-spectral prior for super-resolution of hyperspectral imagery publication-title: IEEE Trans. Comput. Imaging doi: 10.1109/TCI.2020.2996075 contributor: fullname: Jiang – volume: 9 start-page: 1089 issue: 6 year: 2017 ident: 10.1016/j.cviu.2022.103603_b10 article-title: Learning discriminative sparse representations for hyperspectral image classification publication-title: IEEE J. Sel. Top. Sign. Proces. doi: 10.1109/JSTSP.2015.2423260 contributor: fullname: Du – volume: 24 start-page: 4109 issue: 11 year: 2015 ident: 10.1016/j.cviu.2022.103603_b36 article-title: Fast fusion of multi-band images based on solving a sylvester equation publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2015.2458572 contributor: fullname: Wei – volume: 25 start-page: 2249 issue: 5 year: 2016 ident: 10.1016/j.cviu.2022.103603_b42 article-title: Hyperspectral image target detection improvement based on total variation publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2016.2545248 contributor: fullname: Yang – volume: 60 year: 2022 ident: 10.1016/j.cviu.2022.103603_b40 article-title: Diagonalized low-rank learning for hyperspectral image classification publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2021.3085672 contributor: fullname: Xing – volume: 402 start-page: 437 year: 2020 ident: 10.1016/j.cviu.2022.103603_b39 article-title: Using taylor expansion and convolutional sparse representation for image fusion publication-title: Neurocomputing doi: 10.1016/j.neucom.2020.04.002 contributor: fullname: Xing – volume: 53 start-page: 3373 issue: 6 year: 2015 ident: 10.1016/j.cviu.2022.103603_b25 article-title: A convex formulation for hyperspectral image superresolution via subspace-based regularization publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2014.2375320 contributor: fullname: Simes – volume: 3 start-page: 27 issue: 3 year: 2015 ident: 10.1016/j.cviu.2022.103603_b22 article-title: Hyperspectral pansharpening: a review publication-title: IEEE Geosci. Remote Sens. Mag. doi: 10.1109/MGRS.2015.2440094 contributor: fullname: Loncan – volume: 142 start-page: 344 year: 2018 ident: 10.1016/j.cviu.2022.103603_b41 article-title: Hyperspectral image classification via a random patches network publication-title: ISPRS J. Photogramm. Remote Sens. doi: 10.1016/j.isprsjprs.2018.05.014 contributor: fullname: Xu – volume: 86 start-page: 572 issue: 3 year: 2006 ident: 10.1016/j.cviu.2022.103603_b27 article-title: Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit publication-title: Signal Process. doi: 10.1016/j.sigpro.2005.05.030 contributor: fullname: Tropp – volume: 1 start-page: 228 issue: 3 year: 2008 ident: 10.1016/j.cviu.2022.103603_b1 article-title: Sparse and redundant modeling of image content using an image-signature-dictionary publication-title: SIAM J. Imaging Sci. doi: 10.1137/07070156X contributor: fullname: Aharon – volume: 273 start-page: 171 year: 2018 ident: 10.1016/j.cviu.2022.103603_b13 article-title: Super-resolution of hyperspectral image via superpixel-based sparse representation publication-title: Neurocomputing doi: 10.1016/j.neucom.2017.08.019 contributor: fullname: Fang – ident: 10.1016/j.cviu.2022.103603_b43 doi: 10.1007/978-3-030-58526-6_13 – volume: 56 start-page: 3 issue: 1 year: 2018 ident: 10.1016/j.cviu.2022.103603_b11 article-title: ST-IRGS: A region-based self-training algorithm applied to hyperspectral image classification and segmentation publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2017.2713123 contributor: fullname: Fan – volume: 25 start-page: 2337 issue: 5 year: 2016 ident: 10.1016/j.cviu.2022.103603_b9 article-title: Hyperspectral image super-resolution via non-negative structured sparse representation publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2016.2542360 contributor: fullname: Dong – volume: 50 start-page: 7236 issue: 2 year: 2016 ident: 10.1016/j.cviu.2022.103603_b35 article-title: Multi-band image fusion based on spectral unmixing publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2016.2598784 contributor: fullname: Wei – volume: 50 start-page: 528 issue: 2 year: 2012 ident: 10.1016/j.cviu.2022.103603_b45 article-title: Coupled nonnegative matrix factorization unmixing for hyperspectral and multispectral data fusion publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2011.2161320 contributor: fullname: Yokoya – volume: 18 start-page: 148 issue: 1 year: 2014 ident: 10.1016/j.cviu.2022.103603_b26 article-title: Spatio-spectral fusion of satellite images based on dictionary-pair learning publication-title: Inf. Fusion doi: 10.1016/j.inffus.2013.08.005 contributor: fullname: Song – volume: 32 start-page: 1708 issue: 4 year: 2022 ident: 10.1016/j.cviu.2022.103603_b32 article-title: Hyperspectral image super-resolution via deep prior regularization with parameter estimation publication-title: IEEE Trans. Circuits Syst. Video Technol. doi: 10.1109/TCSVT.2021.3078559 contributor: fullname: Wang – start-page: 69 year: 1994 ident: 10.1016/j.cviu.2022.103603_b6 article-title: Watershed, hierarchical segmentation and waterfall algorithm contributor: fullname: Beucher – volume: 53 start-page: 3658 issue: 7 year: 2015 ident: 10.1016/j.cviu.2022.103603_b34 article-title: Hyperspectral and multispectral image fusion based on a sparse representation publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2014.2381272 contributor: fullname: Wei – volume: 56 start-page: 3861 issue: 7 year: 2018 ident: 10.1016/j.cviu.2022.103603_b48 article-title: Hybrid unmixing based on adaptive region segmentation for hyperspectral imagery publication-title: IEEE Trans. Geosci. Remote Sens. doi: 10.1109/TGRS.2018.2815044 contributor: fullname: Zhang – volume: 27 start-page: 4118 issue: 8 year: 2018 ident: 10.1016/j.cviu.2022.103603_b20 article-title: Fusing hyperspectral and multispectral images via coupled sparse tensor factorization publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2018.2836307 contributor: fullname: Li – ident: 10.1016/j.cviu.2022.103603_b30 doi: 10.1109/IGARSS.2014.6947018 – ident: 10.1016/j.cviu.2022.103603_b47 – volume: 36 start-page: 2031 issue: 10 year: 2017 ident: 10.1016/j.cviu.2022.103603_b4 article-title: PVR: Patch-to-volume reconstruction for large area motion correction of fetal MRI publication-title: IEEE Trans. Med. Imaging doi: 10.1109/TMI.2017.2737081 contributor: fullname: Alansary – ident: 10.1016/j.cviu.2022.103603_b7 doi: 10.1109/CVPR.2017.411 |
| SSID | ssj0011491 |
| Score | 2.4363232 |
| Snippet | Hyperspectral image (HSI) super-solution to reconstruct high spatial resolution HSIs has attracted increasing interest in recent years. In this paper, we... |
| SourceID | crossref elsevier |
| SourceType | Aggregation Database Publisher |
| StartPage | 103603 |
| SubjectTerms | Hyperspectral image super-resolution Morphology segmentation Multi-label fusion Sparse coding |
| Title | Sparse coding with morphology segmentation and multi-label fusion for hyperspectral image super-resolution |
| URI | https://dx.doi.org/10.1016/j.cviu.2022.103603 |
| Volume | 227 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV07T8MwED6VdoGBRwFRHpUHNhTaNLaTjFUFKiC6lErdovgFrWha9cHIb-ecOKgwMLCeZMm6O5_v-3znA7jmhoUBFwJBTiw8GjLpRbEJvTDiQWqEZFxYHvJ5wPsj-jhm4wr0yl4YW1bpYn8R0_No7SQtp83WYjJpDRG4hEFOYdjJcnZybS1_JKpCrfvw1B98PyYgCPCL0kNLydGO650pyrzkx2SDMLHTse3nvJyd9ft-2rpz7g9h3yWLpFvs5wgqOqvDgUsciTuWKxSVsxlKWR32tj4aPIbpcIEAVhM5t1cVseQrmc1RxTmpTlb6deZ6kDKSZorkZYYeOoh-J2ZjCTWCyS15Q9Ba9GYucVuTGcYistqgzEPQ7nz4BEb3dy-9vuemLHgyaLfXnlTCp6FWmGcolTITRdpXKgg1VUZaAIuH1JdM0kinQsaKM8XRijFNO0xJEQenUM3mmT4DEmgRGRUwHcaapvajecmNMBFlcapQ3Q24KXWbLIrPNJKyymyaWEsk1hJJYYkGsFL9yQ-XSDDa_7Hu_J_rLmDXzpIv-JVLqK6XG32FGcdaNGHn9tNvOr_6AuDn2HI |
| link.rule.ids | 315,783,787,4511,24130,27938,27939,45599,45693 |
| linkProvider | Elsevier |
| linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV07b8IwELZQGdoOfdBWpU8P3aoIkthOMiJUBOWxABJbFL9aUAkISH9_z4lT0Q4dup5kybo7n-_7fOdD6IlpGviMcwA5EXdIQIUTRjpwgpD5ieaCMm54yOGIdafkdUZnFdQue2FMWaWN_UVMz6O1lTSsNhvr-bwxBuAS-DmFYSbLmcm1VcgGInD2aqvX746-HxMABLhF6aGh5Ihne2eKMi_xOc8AJnqeaT9n5eys3_fT3p3TOUMnNlnErWI_56ii0ho6tYkjtsdyC6JyNkMpq6HjvY8GL9BivAYAq7BYmasKG_IVL1eg4pxUx1v1trQ9SClOUonzMkMHHER9YJ0ZQg1DcovfAbQWvZkb2NZ8CbEIbzOQOQDarQ9fomnnZdLuOnbKgiP8ZnPnCMldEigJeYaUCdVhqFwp_UARqYUBsHBIXUEFCVXCRSQZlQysGJHEo1LwyL9CB-kqVdcI-4qHWvpUBZEiifloXjDNdUholEhQdx09l7qN18VnGnFZZbaIjSViY4m4sEQd0VL98Q-XiCHa_7Hu5p_rHtFhdzIcxIPeqH-Ljsxc-YJruUMHu02m7iH72PEH611fNgbabw |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Sparse+coding+with+morphology+segmentation+and+multi-label+fusion+for+hyperspectral+image+super-resolution&rft.jtitle=Computer+vision+and+image+understanding&rft.au=Xing%2C+Changda&rft.au=Wang%2C+Meiling&rft.au=Cong%2C+Yuhua&rft.au=Wang%2C+Zhisheng&rft.date=2023-01-01&rft.pub=Elsevier+Inc&rft.issn=1077-3142&rft.eissn=1090-235X&rft.volume=227&rft_id=info:doi/10.1016%2Fj.cviu.2022.103603&rft.externalDocID=S1077314222001813 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1077-3142&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1077-3142&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1077-3142&client=summon |