{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T00:51:15Z","timestamp":1760403075959,"version":"build-2065373602"},"reference-count":32,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2021,4,11]],"date-time":"2021-04-11T00:00:00Z","timestamp":1618099200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science and Technology Program of Sichuan","award":["2020YFG0240"],"award-info":[{"award-number":["2020YFG0240"]}]},{"name":"Science and Technology Program of Hebei","award":["20355901D","19255901D"],"award-info":[{"award-number":["20355901D","19255901D"]}]},{"name":"National Defense Science and Technology Key Laboratory of Remote Sensing Information and Image Analysis Technology of China","award":["6142A010301"],"award-info":[{"award-number":["6142A010301"]}]},{"name":"Chinese Air-Force Equipment Pre-Research Project","award":["10305***02"],"award-info":[{"award-number":["10305***02"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Since technologies in image fusion, image splicing, and target recognition have developed rapidly, as the basis of many image applications, the performance of image registration directly affects subsequent work. In this work, for rich features of satellite-borne optical imagery such as panchromatic and multispectral images, the Harris corner algorithm is combined with the scale invariant feature transform (SIFT) operator for feature point extraction. Our rough matching strategy uses the K-D (K-Dimensional) tree combined with the BBF (Best Bin First) method, and the similarity measure is the nearest neighbor\/the second-nearest neighbor ratio. Finally, a triangle-area representation (TAR) algorithm is utilized to eliminate false matches in order to ensure registration accuracy. The performance of the proposed algorithm is compared with existing popular algorithms. The experimental results indicate that for visible light and multi-spectral satellite remote sensing images of different sizes and different sources, the proposed algorithm in this work is excellent in accuracy and efficiency.<\/jats:p>","DOI":"10.3390\/s21082695","type":"journal-article","created":{"date-parts":[[2021,4,12]],"date-time":"2021-04-12T05:52:00Z","timestamp":1618206720000},"page":"2695","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Satellite-Borne Optical Remote Sensing Image Registration Based on Point Features"],"prefix":"10.3390","volume":"21","author":[{"given":"Xinan","family":"Hou","sequence":"first","affiliation":[{"name":"School of Electronic Engineering, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Quanxue","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Telecommunications Engineering, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rong","family":"Wang","sequence":"additional","affiliation":[{"name":"Yangtze Delta Region Institute (HuZhou), University of Electronic Science and Technology of China, Huzhou 313099, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9534-592X","authenticated-orcid":false,"given":"Xin","family":"Luo","sequence":"additional","affiliation":[{"name":"Yangtze Delta Region Institute (HuZhou), University of Electronic Science and Technology of China, Huzhou 313099, China"},{"name":"School of Resources and Environment, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1080\/2150704X.2021.1884916","article-title":"A Remote sensing image registration algorithm based on multiple constraints and a variational Bayesian framework","volume":"12","author":"Gu","year":"2021","journal-title":"Remote Sens. Lett."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1109\/LGRS.2014.2346398","article-title":"Joint image registration and fusion for panchromatic and multispectral images","volume":"12","author":"Zhang","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3584","DOI":"10.1109\/TIP.2019.2899947","article-title":"Fast and robust symmetric image registration based on distances combining intensity and spatial information","volume":"28","author":"Lindblad","year":"2019","journal-title":"IEEE Trans. Image Process."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"4834","DOI":"10.1109\/TGRS.2019.2893310","article-title":"A novel two-step registration method for remote sensing images based on deep and local features","volume":"57","author":"Ma","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.patrec.2018.03.022","article-title":"Extreme-constrained spatial-spectral corner detector for image-level hyperspectral image classification","volume":"109","author":"Li","year":"2018","journal-title":"Pattern Recognit. Lett."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1109\/LGRS.2016.2600858","article-title":"Remote sensing image registration with modified sift and enhanced feature matching","volume":"14","author":"Ma","year":"2017","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.jpdc.2021.02.014","article-title":"Distributed programming of a hyperspectral image registration algorithm for heterogeneous GPU clusters","volume":"151","author":"Gonzalez","year":"2021","journal-title":"J. Parallel Distrib. Comput."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.isprsjprs.2017.11.019","article-title":"Uniform competency-based local feature extraction for remote sensing images","volume":"135","author":"Sedaghat","year":"2018","journal-title":"ISPRS J. Photogram. Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1109\/TIP.2014.2371234","article-title":"Weighted guided image filtering","volume":"24","author":"Li","year":"2015","journal-title":"IEEE Trans. Image Process."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Versaci, M., and Morabito, F.C. (2021). Image edge detection: A new approach based on fuzzy entropy and fuzzy divergence. Int. J. Fuzzy Syst., 1\u201310.","DOI":"10.1007\/s40815-020-01030-5"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"18839","DOI":"10.1007\/s11042-020-08699-8","article-title":"An image segmentation approach based on fuzzy c-means and dynamic particle swarm optimization algorithm","volume":"79","author":"Dhanachandra","year":"2020","journal-title":"Multimed. Tools Appl."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3078","DOI":"10.1109\/TGRS.2018.2790483","article-title":"OS-SIFT: A Robust SIFT-like algorithm for high-resolution optical-to-SAR image registration in suburban areas","volume":"56","author":"Xiang","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"5254","DOI":"10.1109\/TGRS.2019.2959606","article-title":"A new sample consensus based on sparse coding for improved matching of SIFT features on remote sensing images","volume":"58","author":"Etezadifar","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3904","DOI":"10.1109\/TGRS.2018.2888985","article-title":"A contrario comparison of local descriptors for change detection in very high spatial resolution satellite images of urban areas","volume":"57","author":"Liu","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"562","DOI":"10.1109\/LGRS.2014.2351396","article-title":"SAR Image registration using phase congruency and nonlinear diffusion-based SIFT","volume":"12","author":"Fan","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.cviu.2018.01.001","article-title":"Hierarchical semantic image matching using CNN feature pyramid","volume":"169","author":"Yu","year":"2018","journal-title":"Comput. Vis. Image Understand."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Qian, X.L., Lin, S., Cheng, G., Yao, X.W., Ren, H.L., and Wang, W. (2020). Object detection in remote sensing images based on improved bounding box regression and multi-level features fusion. Remote Sens., 12.","DOI":"10.3390\/rs12010143"},{"key":"ref_18","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_19","doi-asserted-by":"crossref","first-page":"506","DOI":"10.1080\/01431161.2018.1513666","article-title":"Very high resolution remote sensing image classification with SEEDS-CNN and scale effect analysis for superpixel CNN classification","volume":"40","author":"Lv","year":"2018","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"69333","DOI":"10.1109\/ACCESS.2020.2986245","article-title":"A Privacy-Preserving and Efficient k-nearest neighbor query and classification scheme based on k-dimensional tree for outsourced data","volume":"8","author":"Du","year":"2020","journal-title":"IEEE Access"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Li, S., Wang, J., Liang, Z., and Su, L. (2016, January 10\u201315). Tree point clouds registration using an improved ICP algorithm based on kd-tree. Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Beijing, China.","DOI":"10.1109\/IGARSS.2016.7730186"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1210","DOI":"10.1109\/LGRS.2019.2896341","article-title":"Multimodal remote sensing image registration based on image transfer and local features","volume":"16","author":"Zhang","year":"2019","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"68638","DOI":"10.1109\/ACCESS.2020.2986498","article-title":"Affine geometrical region CNN for object tracking","volume":"8","author":"Xie","year":"2020","journal-title":"IEEE Access"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1675","DOI":"10.1109\/TIP.2018.2881829","article-title":"On-device scalable image-based localization via prioritized cascade search and fast one-many RANSAC","volume":"28","author":"Tran","year":"2019","journal-title":"IEEE Trans. Image Process."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"5940","DOI":"10.1109\/TSP.2020.3029884","article-title":"Variable step-size widely linear complex-valued affine projection algorithm and performance analysis","volume":"68","author":"Shi","year":"2020","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"6423","DOI":"10.1109\/TSP.2017.2742987","article-title":"Distributed affine projection algorithm over acoustically coupled sensor networks","volume":"65","author":"Ferrer","year":"2017","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"66963","DOI":"10.1109\/ACCESS.2018.2878147","article-title":"An efficient image matching algorithm based on adaptive threshold and RANSAC","volume":"6","author":"Li","year":"2018","journal-title":"IEEE Access"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"4143","DOI":"10.1109\/TGRS.2015.2391999","article-title":"A novel subpixel phase correlation method using singular value decomposition and unified random sample consensus","volume":"53","author":"Tong","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Morley, D., and Foroosh, H. (2017, January 21\u201326). Improving RANSAC-based segmentation through CNN encapsulation. Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.285"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1109\/LGRS.2013.2267771","article-title":"A robust point-matching algorithm for remote sensing image registration","volume":"11","author":"Zhang","year":"2014","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Wang, X., Lv, X., Li, L., Cui, G., and Zhang, Z. (2018, January 6\u20138). A new method of speeded up robust features image registration based on image preprocessing. Proceedings of the 2018 International Conference on Information Systems and Computer Aided Education (ICISCAE), Changchun, China.","DOI":"10.1109\/ICISCAE.2018.8666894"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Yeh, C., Chang, Y., Hsu, P., and Hsien, C. (2018, January 22\u201327). GPU Acceleration of UAV image splicing using oriented fast and rotated brief combined with PCA. Proceedings of the IGARSS 2018\u20142018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8519046"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/8\/2695\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T14:28:00Z","timestamp":1760365680000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/8\/2695"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,11]]},"references-count":32,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2021,4]]}},"alternative-id":["s21082695"],"URL":"https:\/\/doi.org\/10.3390\/s21082695","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2021,4,11]]}}}