{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T12:53:15Z","timestamp":1770900795168,"version":"3.50.1"},"reference-count":47,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2024,3,31]],"date-time":"2024-03-31T00:00:00Z","timestamp":1711843200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key Research Program of Frontier Sciences, Chinese Academy of Sciences","award":["ZDBS-LY-JSC036"],"award-info":[{"award-number":["ZDBS-LY-JSC036"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The surge in remote sensing satellites and diverse imaging modes poses substantial challenges for ground systems. Swift and high-precision geolocation is the foundational requirement for subsequent remote sensing image applications. Breakthroughs in intelligent on-orbit processing now enable on-orbit geometric processing. In the absence of control data on board, a recent trend is to introduce reference data onto satellites. However, the pre-storage of traditional reference images or control point databases presents a significant challenge to the limited on-board data storage capacity. Therefore, oriented to the demand for control information acquisition during on-orbit geometry processing, we propose the construction of lightweight and stable feature databases. Initially, stable feature classes are obtained through iterative matching filtering, followed by re-extracting feature descriptors for each stable feature point location on the training images. Subsequently, the descriptors of each point location are clustered and fused using affinity propagation (AP) to eliminate redundancy. Finally, LDAHash is utilized to quantize floating-point descriptors into binary descriptors, further reducing the storage space. In our experiments, we utilize a variety of feature algorithms to assess the generality of our proposed method, thus extending the scope of the feature database and its applicability to various scenarios. This work plays a crucial role in advancing the technology of on-orbit geometry processing for remote sensing satellites.<\/jats:p>","DOI":"10.3390\/rs16071237","type":"journal-article","created":{"date-parts":[[2024,3,31]],"date-time":"2024-03-31T13:28:00Z","timestamp":1711891680000},"page":"1237","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Lightweight and Stable Multi-Feature Databases for Efficient Geometric Localization of Remote Sensing Images"],"prefix":"10.3390","volume":"16","author":[{"given":"Zilu","family":"Zhao","sequence":"first","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 101408, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6494-3639","authenticated-orcid":false,"given":"Feng","family":"Wang","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing 100190, China"}]},{"given":"Hongjian","family":"You","sequence":"additional","affiliation":[{"name":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China"},{"name":"Key Laboratory of Technology in Geo-Spatial Information Processing and Application System, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 101408, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/s11554-008-0106-9","article-title":"Fast real-time onboard processing of hyperspectral imagery for detection and classification","volume":"4","author":"Du","year":"2009","journal-title":"J. Real-Time Image Process."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"7815","DOI":"10.1109\/TGRS.2020.2984533","article-title":"Block Adjustment With Relaxed Constraints From Reference Images of Coarse Resolution","volume":"58","author":"Long","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"112203","DOI":"10.1109\/ACCESS.2020.3002829","article-title":"Method for the Automatic Generation and Application of Landmark Control Point Library","volume":"8","author":"Lai","year":"2020","journal-title":"IEEE Access"},{"key":"ref_4","first-page":"64","article-title":"On-orbit geometric calibration of Linear push-broom optical satellite based on sparse GCPs","volume":"3","author":"Pi","year":"2020","journal-title":"J. Geod. Geoinf. Sci."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"559","DOI":"10.14358\/PERS.80.6.559-570","article-title":"Planar block adjustment and orthorectification of ZY-3 satellite images","volume":"80","author":"Wang","year":"2014","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3350","DOI":"10.1109\/JSTARS.2020.2998838","article-title":"Ground control point automatic extraction for spaceborne georeferencing based on FPGA","volume":"13","author":"Liu","year":"2020","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1007\/s11554-017-0741-0","article-title":"Embedded GPU implementation of sensor correction for on-board real-time stream computing of high-resolution optical satellite imagery","volume":"15","author":"Wang","year":"2018","journal-title":"J. Real-Time Image Process."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Salazar, C., Gonzalez-Llorente, J., Cardenas, L., Mendez, J., Rincon, S., Rodriguez-Ferreira, J., and Acero, I.F. (2022). Cloud Detection Autonomous System Based on Machine Learning and COTS Components On-Board Small Satellites. Remote Sens., 14.","DOI":"10.3390\/rs14215597"},{"key":"ref_9","first-page":"195","article-title":"A fast geometric rectification of remote sensing imagery based on feature ground control point database","volume":"8","author":"Yang","year":"2009","journal-title":"WSEAS Trans. Comput."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Bay, H., Tuytelaars, T., and Van Gool, L. (2006, January 7\u201313). Surf: Speeded up robust features. Proceedings of the Computer Vision\u2013ECCV 2006: 9th European Conference on Computer Vision, Graz, Austria. Proceedings, Part I 9.","DOI":"10.1007\/11744023_32"},{"key":"ref_11","first-page":"413","article-title":"Spaceborne lightweight image control points generation method","volume":"51","author":"Ji","year":"2022","journal-title":"Acta Geod. Et Cartogr. Sin."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","article-title":"Distinctive image features from scale-invariant keypoints","volume":"60","author":"Lowe","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Kelman, A., Sofka, M., and Stewart, C.V. (2007, January 17\u201322). Keypoint descriptors for matching across multiple image modalities and non-linear intensity variations. Proceedings of the 2007 IEEE Conference on Computer Vision and Pattern recognition, Minneapolis, MN, USA.","DOI":"10.1109\/CVPR.2007.383426"},{"key":"ref_14","unstructured":"Schowengerdt, R.A. (2007). Remote Sensing (Third Edition), Academic Press."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.isprsjprs.2019.03.002","article-title":"Robust registration for remote sensing images by combining and localizing feature-and area-based methods","volume":"151","author":"Feng","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"4516","DOI":"10.1109\/TGRS.2011.2144607","article-title":"Uniform robust scale-invariant feature matching for optical remote sensing images","volume":"49","author":"Sedaghat","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Alcantarilla, P.F., Bartoli, A., and Davison, A.J. (2012, January 7\u201313). KAZE features. Proceedings of the Computer Vision\u2013ECCV 2012: 12th European Conference on Computer Vision, Florence, Italy. Proceedings, Part VI 12.","DOI":"10.1007\/978-3-642-33783-3_16"},{"key":"ref_18","first-page":"1281","article-title":"Fast explicit diffusion for accelerated features in nonlinear scale spaces","volume":"34","author":"Alcantarilla","year":"2011","journal-title":"IEEE Trans. Patt. Anal. Mach. Intell"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1615","DOI":"10.1109\/TPAMI.2005.188","article-title":"A performance evaluation of local descriptors","volume":"27","author":"Mikolajczyk","year":"2005","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"815","DOI":"10.1109\/TPAMI.2009.77","article-title":"Daisy: An efficient dense descriptor applied to wide-baseline stereo","volume":"32","author":"Tola","year":"2009","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"5283","DOI":"10.1109\/TGRS.2015.2420659","article-title":"Remote sensing image matching based on adaptive binning SIFT descriptor","volume":"53","author":"Sedaghat","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Rublee, E., Rabaud, V., Konolige, K., and Bradski, G. (2011, January 6\u201313). ORB: An efficient alternative to SIFT or SURF. Proceedings of the 2011 International Conference on Computer Vision, Barcelona, Spain.","DOI":"10.1109\/ICCV.2011.6126544"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Leutenegger, S., Chli, M., and Siegwart, R.Y. (2011, January 6\u201313). BRISK: Binary robust invariant scalable keypoints. Proceedings of the 2011 International Conference on Computer Vision, Barcelona, Spain.","DOI":"10.1109\/ICCV.2011.6126542"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Alahi, A., Ortiz, R., and Vandergheynst, P. (2012, January 16\u201321). Freak: Fast retina keypoint. Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, Providence, RI, USA.","DOI":"10.1109\/CVPR.2012.6247715"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1109\/MGRS.2021.3081763","article-title":"Advances and opportunities in remote sensing image geometric registration: A systematic review of state-of-the-art approaches and future research directions","volume":"9","author":"Feng","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2941","DOI":"10.1109\/TGRS.2017.2656380","article-title":"Robust registration of multimodal remote sensing images based on structural similarity","volume":"55","author":"Ye","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"5368","DOI":"10.1109\/TGRS.2018.2815523","article-title":"SAR and optical image registration using nonlinear diffusion and phase congruency structural descriptor","volume":"56","author":"Fan","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3296","DOI":"10.1109\/TIP.2019.2959244","article-title":"RIFT: Multi-modal image matching based on radiation-variation insensitive feature transform","volume":"29","author":"Li","year":"2019","journal-title":"IEEE Trans. Image Process."},{"key":"ref_29","unstructured":"Viswanathan, D.G. (2009, January 6\u20138). Features from accelerated segment test (fast). Proceedings of the 10th Workshop on Image Analysis for Multimedia Interactive Services, London, UK."},{"key":"ref_30","first-page":"147","article-title":"A combined corner and edge detector","volume":"Volume 15","author":"Harris","year":"1988","journal-title":"Proceedings of the Alvey Vision Conference"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1561\/0600000017","article-title":"Local invariant feature detectors: A survey","volume":"3","author":"Tuytelaars","year":"2008","journal-title":"Found. Trends\u00ae Comput. Graph. Vis."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Tuytelaars, T., Van Gool, L., Mirmehdi, M., and Thomas, B.T. (2000, January 11\u201314). Wide baseline stereo matching based on local, affinely invariant regions. Proceedings of the BMVC, Bristol, UK.","DOI":"10.5244\/C.14.38"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1023\/B:VISI.0000020671.28016.e8","article-title":"Matching widely separated views based on affine invariant regions","volume":"59","author":"Tuytelaars","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"761","DOI":"10.1016\/j.imavis.2004.02.006","article-title":"Robust wide-baseline stereo from maximally stable extremal regions","volume":"22","author":"Matas","year":"2004","journal-title":"Image Vis. Comput."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1179\/1743131X12Y.0000000046","article-title":"Multi-spectral image registration and evaluation based on edge-enhanced MSER","volume":"62","author":"Liu","year":"2014","journal-title":"Imaging Sci. J."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.patrec.2016.01.003","article-title":"On the completeness of feature-driven maximally stable extremal regions","volume":"74","author":"Martins","year":"2016","journal-title":"Pattern Recognit. Lett."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2475","DOI":"10.1109\/JSTARS.2023.3344474","article-title":"Robust Region Feature Extraction with Salient MSER and Segment Distance-weighted GLOH for Remote Sensing Image Registration","volume":"17","author":"Zhao","year":"2023","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"12061","DOI":"10.1109\/JSTARS.2021.3129099","article-title":"HSI-MSER: Hyperspectral Image Registration Algorithm Based on MSER and SIFT","volume":"14","author":"Heras","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"\u015aluzek, A. (15\u201316, January 8\u201310). Improving performances of MSER features in matching and retrieval tasks. Proceedings of the Computer Vision\u2013ECCV 2016 Workshops, Amsterdam, The Netherlands. Proceedings, Part III 14.","DOI":"10.1007\/978-3-319-49409-8_63"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.imavis.2015.01.008","article-title":"Registration of images with affine geometric distortion based on maximally stable extremal regions and phase congruency","volume":"36","author":"Zhang","year":"2015","journal-title":"Image Vis. Comput."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Guo, Y., and Gu, Y. (2009, January 12\u201317). Robust feature matching and selection methods for multisensor image registration. Proceedings of the 2009 IEEE International Geoscience and Remote Sensing Symposium, Cape Town, South Africa.","DOI":"10.1109\/IGARSS.2009.5417786"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Zhao, Z., Long, H., and You, H. (2023). An Optical Remote Sensing Image Matching Method Based on the Simple and Stable Feature Database. Appl. Sci., 13.","DOI":"10.3390\/app13074632"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"972","DOI":"10.1126\/science.1136800","article-title":"Clustering by passing messages between data points","volume":"315","author":"Frey","year":"2007","journal-title":"Science"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1109\/TPAMI.2011.103","article-title":"LDAHash: Improved matching with smaller descriptors","volume":"34","author":"Strecha","year":"2011","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3304","DOI":"10.1109\/JSTARS.2015.2475133","article-title":"Hierarchical filtering strategy for registration of remote sensing images of coral reefs","volume":"9","author":"Cheng","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1577","DOI":"10.1109\/TGRS.2020.3001089","article-title":"Robust feature matching for remote sensing image registration via linear adaptive filtering","volume":"59","author":"Jiang","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1109\/JSTARS.2023.3330745","article-title":"Potential of GNSS-R for the Monitoring of Lake Ice Phenology","volume":"17","author":"Ghiasi","year":"2023","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/7\/1237\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:21:48Z","timestamp":1760106108000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/7\/1237"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,31]]},"references-count":47,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2024,4]]}},"alternative-id":["rs16071237"],"URL":"https:\/\/doi.org\/10.3390\/rs16071237","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3,31]]}}}