{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T16:39:02Z","timestamp":1769877542328,"version":"3.49.0"},"reference-count":41,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2020,12,9]],"date-time":"2020-12-09T00:00:00Z","timestamp":1607472000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No. 41771479"],"award-info":[{"award-number":["No. 41771479"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National High-Resolution Earth Observation System (the Civil Part)","award":["No. 50-H31D01-0508-13\/15"],"award-info":[{"award-number":["No. 50-H31D01-0508-13\/15"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Image stitching based on a global alignment model is widely used in computer vision. However, the resulting stitched image may look blurry or ghosted due to parallax. To solve this problem, we propose a parallax-tolerant image stitching method based on nonrigid warping in this paper. Given a group of putative feature correspondences between overlapping images, we first use a semiparametric function fitting, which introduces a motion coherence constraint to remove outliers. Then, the input images are warped according to a nonrigid warp model based on Gaussian radial basis functions. The nonrigid warping is a kind of elastic deformation that is flexible and smooth enough to eliminate moderate parallax errors. This leads to high-precision alignment in the overlapped region. For the nonoverlapping region, we use a rigid similarity model to reduce distortion. Through effective transition, the nonrigid warping of the overlapped region and the rigid warping of the nonoverlapping region can be used jointly. Our method can obtain more accurate local alignment while maintaining the overall shape of the image. Experimental results on several challenging data sets for urban scene show that the proposed approach is better than state-of-the-art approaches in both qualitative and quantitative indicators.<\/jats:p>","DOI":"10.3390\/s20247050","type":"journal-article","created":{"date-parts":[[2020,12,9]],"date-time":"2020-12-09T09:17:58Z","timestamp":1607505478000},"page":"7050","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Image Stitching Based on Nonrigid Warping for Urban Scene"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6966-8303","authenticated-orcid":false,"given":"Lixia","family":"Deng","sequence":"first","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiuxiao","family":"Yuan","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8151-8183","authenticated-orcid":false,"given":"Cailong","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7825-6194","authenticated-orcid":false,"given":"Jun","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Cai","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Li, G., Ji, X., and Zhang, M. (2018). Image Stitching in Smog Weather based on MSR and SURF. Int. J. Perform. Eng., 14.","DOI":"10.23940\/ijpe.18.09.p28.21892196"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Yuan, S., Yang, K., Li, X., and Cai, H. (2020). Automatic Seamline Determination for Urban Image Mosaicking Based on Road Probability Map from the D-LinkNet Neural Network. Sensors, 20.","DOI":"10.3390\/s20071832"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Li, L., Yao, J., Xie, R., Xia, M., and Zhang, W. (2017). A unified framework for street-view panorama stitching. Sensors, 17.","DOI":"10.3390\/s17010001"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Zhang, W., Li, M., Guo, B., Li, D., and Guo, G. (2017). Rapid texture optimization of three-dimensional urban model based on oblique images. Sensors, 17.","DOI":"10.3390\/s17040911"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Shao, Z., Yang, N., Xiao, X., Zhang, L., and Peng, Z. (2016). A multi-view dense point cloud generation algorithm based on low-altitude remote sensing images. Remote Sens., 8.","DOI":"10.3390\/rs8050381"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Shao, Z., Li, C., Li, D., Altan, O., Zhang, L., and Ding, L. (2020). An Accurate Matching Method for Projecting Vector Data into Surveillance Video to Monitor and Protect Cultivated Land. ISPRS Int. J. Geo-Inf., 9.","DOI":"10.3390\/ijgi9070448"},{"key":"ref_7","first-page":"1","article-title":"Image alignment and stitching: A tutorial","volume":"2","author":"Szeliski","year":"2006","journal-title":"Found. Trends\u00ae Comput. Graph. Vis."},{"key":"ref_8","unstructured":"Gao, J., Li, Y., Chin, T.J., and Brown, M.S. (2020, November 05). Seam-Driven Image Stitching; Eurographics (Short Papers). Available online: http:\/\/dx.doi.org\/10.2312\/conf\/EG2013\/short\/045-048."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Zhang, F., and Liu, F. (2014, January 23\u201328). Parallax-tolerant image stitching. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Columbus, OH, USA.","DOI":"10.1109\/CVPR.2014.423"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Lin, K., Jiang, N., Cheong, L.F., Do, M., and Lu, J. (2016). Seagull: Seam-guided local alignment for parallax-tolerant image stitching. European Conference on Computer Vision, Springer.","DOI":"10.1007\/978-3-319-46487-9_23"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Herrmann, C., Wang, C., Strong Bowen, R., Keyder, E., Krainin, M., Liu, C., and Zabih, R. (2018, January 8\u201314). Robust image stitching with multiple registrations. Proceedings of the European Conference on Computer Vision (ECCV), Munich, Germany.","DOI":"10.1007\/978-3-030-01216-8_4"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Gao, J., Kim, S.J., and Brown, M.S. (2011, January 20\u201325). Constructing image panoramas using dual-homography warping. Proceedings of the CVPR 2011, Providence, RI, USA.","DOI":"10.1109\/CVPR.2011.5995433"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Lin, W.Y., Liu, S., Matsushita, Y., Ng, T.T., and Cheong, L.F. (2011, January 20\u201325). Smoothly varying affine stitching. Proceedings of the CVPR 2011, Providence, RI, USA.","DOI":"10.1109\/CVPR.2011.5995314"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Zaragoza, J., Chin, T.J., Brown, M.S., and Suter, D. (2013, January 23\u201328). As-projective-as-possible image stitching with moving DLT. Proceedings of the IEEE conference on computer vision and pattern recognition, Portland, OR, USA.","DOI":"10.1109\/CVPR.2013.303"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1109\/TPAMI.2007.70729","article-title":"Image stitching using structure deformation","volume":"30","author":"Jia","year":"2008","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1672","DOI":"10.1109\/TMM.2017.2777461","article-title":"Parallax-tolerant image stitching based on robust elastic warping","volume":"20","author":"Li","year":"2018","journal-title":"IEEE Trans. Multimed."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"4634","DOI":"10.1109\/JSTARS.2019.2947162","article-title":"Drone Image Stitching Based on Compactly Supported Radial Basis Function","volume":"12","author":"Chen","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1145\/358669.358692","article-title":"Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography","volume":"24","author":"Fischler","year":"1981","journal-title":"Commun. ACM"},{"key":"ref_19","unstructured":"Yuille, A.L., and Grzywacz, N.M. (1988, January 5\u20138). The motion coherence theory. Proceedings of the ICCV 1988, Tampa, FL, USA."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Lin, W.Y.D., Cheng, M.M., Lu, J., Yang, H., Do, M.N., and Torr, P. (2014). Bilateral functions for global motion modeling. European Conference on Computer Vision, Springer.","DOI":"10.1007\/978-3-319-10593-2_23"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1109\/TPAMI.2017.2652468","article-title":"CODE: Coherence based decision boundaries for feature correspondence","volume":"40","author":"Lin","year":"2017","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1080\/02664763.2013.838667","article-title":"Image warping using radial basis functions","volume":"41","author":"Chen","year":"2014","journal-title":"J. Appl. Stat."},{"key":"ref_23","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_24","doi-asserted-by":"crossref","first-page":"033011","DOI":"10.1117\/1.JEI.24.3.033011","article-title":"Feature matching for illumination variation images","volume":"24","author":"Shao","year":"2015","journal-title":"J. Electron. Imaging"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"55","DOI":"10.3724\/SP.J.2096-5796.2018.0008","article-title":"A survey on image and video stitching","volume":"1","author":"Wei","year":"2019","journal-title":"Virtual Real. Intell. Hardw."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3099","DOI":"10.1109\/TIP.2016.2535225","article-title":"Multi-viewpoint panorama construction with wide-baseline images","volume":"25","author":"Zhang","year":"2016","journal-title":"IEEE Trans. Image Process."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"5491","DOI":"10.1109\/TIP.2016.2607419","article-title":"Joint video stitching and stabilization from moving cameras","volume":"25","author":"Guo","year":"2016","journal-title":"IEEE Trans. Image Process."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1706","DOI":"10.1109\/TIP.2014.2307478","article-title":"Robust point matching via vector field consensus","volume":"23","author":"Ma","year":"2014","journal-title":"IEEE Trans. Image Process."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Chen, J., Xu, Q., Luo, L., Wang, Y., and Wang, S. (2019). A robust method for automatic panoramic UAV image mosaic. Sensors, 19.","DOI":"10.3390\/s19081898"},{"key":"ref_30","first-page":"1","article-title":"Content-preserving warps for 3D video stabilization","volume":"28","author":"Liu","year":"2009","journal-title":"ACM Trans. Graph. (TOG)"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Herrmann, C., Wang, C., Strong Bowen, R., Keyder, E., and Zabih, R. (2018, January 8\u201314). Object-centered image stitching. Proceedings of the European Conference on Computer Vision (ECCV), Munich, Germany.","DOI":"10.1007\/978-3-030-01219-9_50"},{"key":"ref_32","unstructured":"Ren, S., He, K., Girshick, R., and Sun, J. (2015, January 7\u201312). Faster r-cnn: Towards real-time object detection with region proposal networks. Proceedings of the Advances in Neural Information Processing Systems, Montreal, QC, Canada."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Chang, C.H., Sato, Y., and Chuang, Y.Y. (2014, January 23\u201328). Shape-preserving half-projective warps for image stitching. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Columbus, OH, USA.","DOI":"10.1109\/CVPR.2014.422"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Lin, C.C., Pankanti, S.U., Natesan Ramamurthy, K., and Aravkin, A.Y. (2015, January 7\u201312). Adaptive as-natural-as-possible image stitching. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Boston, MA, USA.","DOI":"10.1109\/CVPR.2015.7298719"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1365","DOI":"10.1109\/TMM.2017.2771566","article-title":"Quasi-homography warps in image stitching","volume":"20","author":"Li","year":"2018","journal-title":"IEEE Trans. Multimed."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1109\/TIP.2017.2736603","article-title":"Dynamic video stitching via shakiness removing","volume":"27","author":"Nie","year":"2017","journal-title":"IEEE Trans. Image Process."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Myronenko, A., Song, X., and Carreira-Perpin\u00e1n, M.A. (2007, January 3\u20136). Non-rigid point set registration: Coherent point drift. Proceedings of the Advances in Neural Information Processing Systems, Vancouver, BC, Canada.","DOI":"10.7551\/mitpress\/7503.003.0131"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Lin, W.Y., Cheng, M.M., Zheng, S., Lu, J., and Crook, N. (2013, January 1\u20138). Robust non-parametric data fitting for correspondence modeling. Proceedings of the IEEE International Conference on Computer Vision, Sydney, NSW, Australia.","DOI":"10.1109\/ICCV.2013.295"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Rohr, K., Stiehl, H.S., Sprengel, R., Beil, W., Buzug, T.M., Weese, J., and Kuhn, M. (1996, January 22\u201325). Point-based elastic registration of medical image data using approximating thin-plate splines. Proceedings of the International Conference on Visualization in Biomedical Computing, Hamburg, Germany.","DOI":"10.1007\/BFb0046967"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"764","DOI":"10.1016\/j.jesp.2013.03.013","article-title":"Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median","volume":"49","author":"Leys","year":"2013","journal-title":"J. Exp. Soc. Psychol."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Lourakis, M.I. (2010, January 5\u201311). Sparse non-linear least squares optimization for geometric vision. Proceedings of the European Conference on Computer Vision, Crete, Greece.","DOI":"10.1007\/978-3-642-15552-9_4"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/24\/7050\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:42:48Z","timestamp":1760179368000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/20\/24\/7050"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,9]]},"references-count":41,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2020,12]]}},"alternative-id":["s20247050"],"URL":"https:\/\/doi.org\/10.3390\/s20247050","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,12,9]]}}}