{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T03:34:52Z","timestamp":1775446492346,"version":"3.50.1"},"reference-count":35,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2021,1,25]],"date-time":"2021-01-25T00:00:00Z","timestamp":1611532800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Team Project of the Education Ministry of the Guangdong Province","award":["2017KCXTD011"],"award-info":[{"award-number":["2017KCXTD011"]}]},{"name":"Guangdong Higher Education Engineering Technology Research Center for Big Data on Manufacturing Knowledge Patent","award":["501130144"],"award-info":[{"award-number":["501130144"]}]},{"name":"National Nature Science Foundation of China","award":["U1701266, 61372173 and 62071128"],"award-info":[{"award-number":["U1701266, 61372173 and 62071128"]}]},{"name":"Hong Kong Innovation and Technology Commission, Enterprise Support Scheme","award":["S\/E\/070\/17"],"award-info":[{"award-number":["S\/E\/070\/17"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This paper proposes a two dimensional quaternion valued singular spectrum analysis based method for enhancing the hyperspectral image. Here, the enhancement is for performing the object recognition, but neither for improving the visual quality nor suppressing the artifacts. In particular, the two dimensional quaternion valued singular spectrum analysis components are selected in such a way that the ratio of the interclass separation to the intraclass separation of the pixel vectors is maximized. Next, the support vector machine is employed for performing the object recognition. Compared to the conventional two dimensional real valued singular spectrum analysis based method where only the pixels in a color plane is exploited, the two dimensional quaternion valued singular spectrum analysis based method fuses four color planes together for performing the enhancement. Hence, both the spatial information among the pixels in the same color plane and the spectral information among various color planes are exploited. The computer numerical simulation results show that the overall classification accuracy based on our proposed method is higher than the two dimensional real valued singular spectrum analysis based method, the three dimensional singular spectrum analysis based method, the multivariate two dimensional singular spectrum analysis based method, the median filtering based method, the principal component analysis based method, the Tucker decomposition based method and the hybrid spectral convolutional neural network (hybrid SN) based method.<\/jats:p>","DOI":"10.3390\/rs13030405","type":"journal-article","created":{"date-parts":[[2021,1,25]],"date-time":"2021-01-25T09:59:40Z","timestamp":1611568780000},"page":"405","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Hyperspectral Image Enhancement by Two Dimensional Quaternion Valued Singular Spectrum Analysis for Object Recognition"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4375-3515","authenticated-orcid":false,"given":"Yuxin","family":"Lin","sequence":"first","affiliation":[{"name":"School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0633-7224","authenticated-orcid":false,"given":"Bingo Wing-Kuen","family":"Ling","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China"}]},{"given":"Lingyue","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China"}]},{"given":"Yiting","family":"Zheng","sequence":"additional","affiliation":[{"name":"Faculty of Physical Sciences and Engineering, Cardiff University, Cardiff, Wales CF10 3AT, UK"}]},{"given":"Nuo","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China"}]},{"given":"Xueling","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China"}]},{"given":"Xinpeng","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Information Engineering, Guangdong University of Technology, Guangzhou 510006, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,1,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/S0034-4257(99)00067-X","article-title":"Hyperspectral Vegetation Indices and Their Relationships with Agricultural Crop Characteristics","volume":"71","author":"Thenkabail","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_2","first-page":"11725","article-title":"Remote sensing of coccolithophore blooms in selected oceanic regions using the PhytoDOAS method applied to hyper-spectral satellite data","volume":"8","author":"Sadeghi","year":"2011","journal-title":"Biogeoences Discuss."},{"key":"ref_3","first-page":"266","article-title":"N-FINDR: An algorithm for fast autonomous spectral end-member determination in hyperspectral data","volume":"3753","author":"Michael","year":"1999","journal-title":"Proc. Spie Int. Soc. Opt. Eng."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"779","DOI":"10.1109\/36.298007","article-title":"Hyperspectral image classification and dimensionality reduction: An orthogonal subspace projection approach","volume":"32","author":"Joseph","year":"1994","journal-title":"IEEE Trans. Geo. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"608","DOI":"10.1109\/TGRS.2003.819189","article-title":"Estimation of number of spectrally distinct signal sources in hyperspectral imagery","volume":"42","author":"Chang","year":"2004","journal-title":"IEEE Trans. Geoence Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3742","DOI":"10.1109\/TGRS.2013.2275613","article-title":"Feature Extraction of Hyperspectral Images with Image Fusion and Recursive Filtering","volume":"52","author":"Kang","year":"2014","journal-title":"IEEE Trans. Geoence Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1109\/LGRS.2005.846011","article-title":"On the impact of PCA dimension reduction for hyperspectral detection of difficult targets","volume":"2","author":"Farrell","year":"2005","journal-title":"IEEE Geoence Remote Sens. Lett."},{"key":"ref_8","first-page":"3","article-title":"The effectiveness of spectral similarity measures for the analysis of hyperspectral imagery","volume":"8","author":"Meer","year":"2006","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_9","first-page":"1","article-title":"Novel Two-Dimensional Singular Spectrum Analysis for Effective Feature Extraction and Data Classification in Hyperspectral Imaging","volume":"53","author":"Zabalza","year":"2015","journal-title":"IEEE Trans. Geoence Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"652","DOI":"10.1109\/JPROC.2012.2197589","article-title":"Advances in Spectral-Spatial Classification of Hyperspectral Images","volume":"101","author":"Fauvel","year":"2013","journal-title":"Proc. IEEE"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"3660","DOI":"10.1109\/TGRS.2012.2185054","article-title":"Hyperspectral Image Denoising Employing a Spectral\u2013Spatial Adaptive Total Variation Model","volume":"50","author":"Yuan","year":"2012","journal-title":"IEEE Trans. Geoence Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1109\/LGRS.2017.2671439","article-title":"Target Detection for Polarized Hyperspectral Images Based on Tensor Decomposition","volume":"14","author":"Tan","year":"2017","journal-title":"IEEE Geoence Remote Sens. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1109\/LGRS.2019.2918719","article-title":"HybridSN: Exploring 3D-2D CNN Feature Hierarchy for Hyperspectral Image Classification","volume":"17","author":"Roy","year":"2020","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_14","first-page":"564","article-title":"Elements of quaternions","volume":"2","author":"Hardy","year":"1969","journal-title":"Science"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"2783","DOI":"10.1109\/78.960426","article-title":"Efficient implementation of quaternion Fourier transform, convolution, and correlation by 2-D complex FFT","volume":"49","author":"Pei","year":"2001","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1007\/s00006-007-0037-8","article-title":"Quaternion Fourier transform on quaternion fields and generalizations","volume":"17","author":"Hitzer","year":"2007","journal-title":"Adv. Appl. Clifford Algebras"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"634","DOI":"10.1049\/iet-spr.2020.0199","article-title":"Near orthogonal discrete quaternion Fourier transform components via an optimal frequency rescaling approach","volume":"14","author":"Hu","year":"2020","journal-title":"IET Signal Process."},{"key":"ref_18","unstructured":"Lin, Y., Ling, B.W.K., and Xu, N. (2021). Two Dimensional Quaternion Valued Singular Spectrum Analysis with Application to Image Denoising. Circuits Syst. Signal Process., Submitted."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/j.jvcir.2017.08.011","article-title":"Quaternion pseudo-Zernike moments combining both of RGB information and depth information for color image splicing detection","volume":"49","author":"Chen","year":"2017","journal-title":"J. Vis. Commun. Image Represent."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"102131","DOI":"10.1016\/j.bspc.2020.102131","article-title":"Effectiveness analysis of bio-electronic stimulation therapy to Parkinson\u2019s diseases via joint singular spectrum analysis and discrete fourier transform approach","volume":"62","author":"Lin","year":"2020","journal-title":"Biomed. Signal Process. Control"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/0167-2789(92)90103-T","article-title":"Singular-spectrum analysis: A toolkit for short, noisy chaotic signals","volume":"158","author":"Vautard","year":"1992","journal-title":"Physica D"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1190\/1.3552706","article-title":"Simultaneous seismic data denoising and reconstruction via multichannel singular spectrum analysis","volume":"76","author":"Oropeza","year":"2011","journal-title":"Geophysics"},{"key":"ref_23","first-page":"49","article-title":"Basic features of class-I alcohol dehydrogenase: Variable and constant segments coordinated by inter-class and intra-class variability. Conclusions from characterization of the alligator enzyme","volume":"216","author":"Persson","year":"2010","journal-title":"FEBS J."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"5599","DOI":"10.1109\/TIP.2014.2365699","article-title":"Multitask linear discriminant analysis for view invariant action recognition","volume":"23","author":"Yan","year":"2014","journal-title":"IEEE Trans. Image Process. Publ. IEEE Signal Process. Soc."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1109\/LGRS.2005.857031","article-title":"Composite kernels for hyperspectral image classification","volume":"3","author":"Valls","year":"2006","journal-title":"IEEE Geoence Remote Sens. Lett."},{"key":"ref_26","first-page":"393","article-title":"Analytical form of globally optimal solution of weighted sum of intraclass separation and interclass separation","volume":"12","author":"Qing","year":"2017","journal-title":"Signal Image Video Process."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Golyandina, N., Nekrutkin, V., and Zhigljavsky, A. (2001). Analysis of Time Series Structure: SSA and Related Techniques, CRC Press.","DOI":"10.1201\/9781420035841"},{"key":"ref_28","first-page":"403","article-title":"On the choice of parameters in Singular Spectrum Analysis and related subspace-based methods","volume":"1","author":"Golyandina","year":"1930","journal-title":"Stat. Interface"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"727","DOI":"10.1016\/j.amc.2006.04.032","article-title":"Quaternion singular value decomposition based on bidiagonalization to a real or complex matrix using quaternion Householder transformations","volume":"182","author":"Sangwine","year":"2006","journal-title":"Appl. Math. Comput."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"23483","DOI":"10.1007\/s11042-018-5652-y","article-title":"Optimal blind watermarking for color images based on the U matrix of quaternion singular value decomposition","volume":"77","author":"Liu","year":"2018","journal-title":"Multimed. Tools Appl."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Shlemov, A., Golyandina, N., Holloway, D., and Spirov, A. (2015). Shaped 3D singular spectrum analysis for quantifying gene expression, with application to the early zebrafish embroy. BioMed Res. Int., 1\u201318.","DOI":"10.1155\/2015\/986436"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Golyandina, N., Korobeynikov, A., and Zhigljavsky, A. (2018). Singular Spectrum Analysis with R, Springer.","DOI":"10.1007\/978-3-662-57380-8"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1961189.1961199","article-title":"LIBSVM: A library for support vector machines","volume":"2","author":"Chang","year":"2011","journal-title":"ACM Trans. Intell. Syst. Technol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0304-8853(96)00062-5","article-title":"Current-driven excitation of magnetic multilayers","volume":"159","author":"Slonczewski","year":"1996","journal-title":"J. Magn. Magn. Mater."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1137\/07070111X","article-title":"Tensor Decompositions and Applications","volume":"51","author":"Kolda","year":"2009","journal-title":"SIAM Rev."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/3\/405\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:14:53Z","timestamp":1760159693000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/3\/405"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,25]]},"references-count":35,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2021,2]]}},"alternative-id":["rs13030405"],"URL":"https:\/\/doi.org\/10.3390\/rs13030405","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1,25]]}}}