{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T05:28:50Z","timestamp":1780464530532,"version":"3.54.1"},"reference-count":40,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2019,8,6]],"date-time":"2019-08-06T00:00:00Z","timestamp":1565049600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Nature Science Foundation of China","award":["No.61671408"],"award-info":[{"award-number":["No.61671408"]}]},{"name":"the Joint Fund Project of Chinese Ministry of Education","award":["No.6141A02022350, No.6141A02022362"],"award-info":[{"award-number":["No.6141A02022350, No.6141A02022362"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Automatic image registration has been wildly used in remote sensing applications. However, the feature-based registration method is sometimes inaccurate and unstable for images with large scale difference, grayscale and texture differences. In this manuscript, a coarse-to-fine registration scheme is proposed, which combines the advantage of feature-based registration and phase correlation-based registration. The scheme consists of four steps. First, feature-based registration method is adopted for coarse registration. A geometrical outlier removal method is applied to improve the accuracy of coarse registration, which uses geometric similarities of inliers. Then, the sensed image is modified through the coarse registration result under affine deformation model. After that, the modified sensed image is registered to the reference image by extended phase correlation. Lastly, the final registration results are calculated by the fusion of the coarse registration and the fine registration. High universality of feature-based registration and high accuracy of extended phase correlation-based registration are both preserved in the proposed method. Experimental results of several different remote sensing images, which come from several published image registration papers, demonstrate the high robustness and accuracy of the proposed method. The evaluation contains root mean square error (RMSE), Laplace mean square error (LMSE) and red\u2013green image registration results.<\/jats:p>","DOI":"10.3390\/rs11151833","type":"journal-article","created":{"date-parts":[[2019,8,7]],"date-time":"2019-08-07T03:09:08Z","timestamp":1565147348000},"page":"1833","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["A Novel Coarse-to-Fine Scheme for Remote Sensing Image Registration Based on SIFT and Phase Correlation"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7825-0902","authenticated-orcid":false,"given":"Han","family":"Yang","sequence":"first","affiliation":[{"name":"Faculty of Electrical Engineering, Zhejiang University, No. 38, West Lake District, Hangzhou 310000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaorun","family":"Li","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering, Zhejiang University, No. 38, West Lake District, Hangzhou 310000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liaoying","family":"Zhao","sequence":"additional","affiliation":[{"name":"Schoole of Computer Science and Technology, Hangzhou Dianzi University, No.1 Street, Baiyang Street, Hangzhou Economic and Technological Development Zone, Hangzhou 310018, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuhan","family":"Chen","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering, Zhejiang University, No. 38, West Lake District, Hangzhou 310000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,8,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1716","DOI":"10.1109\/LGRS.2016.2605304","article-title":"A Robust Point-Matching Algorithm Based on Integrated Spatial Structure Constraint for Remote Sensing Image Registration","volume":"13","author":"Jiang","year":"2016","journal-title":"IEEE Geosci. 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