{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:57:59Z","timestamp":1760241479273,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2018,4,24]],"date-time":"2018-04-24T00:00:00Z","timestamp":1524528000000},"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":["41201364","31501222"],"award-info":[{"award-number":["41201364","31501222"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2662017JC038"],"award-info":[{"award-number":["2662017JC038"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Innovation Training Plan Program of University Student","award":["201610504017"],"award-info":[{"award-number":["201610504017"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In recent years, digital frame cameras have been increasingly used for remote sensing applications. However, it is always a challenge to align or register images captured with different cameras or different imaging sensor units. In this research, a novel registration method was proposed. Coarse registration was first applied to approximately align the sensed and reference images. Window selection was then used to reduce the search space and a histogram specification was applied to optimize the grayscale similarity between the images. After comparisons with other commonly-used detectors, the fast corner detector, FAST (Features from Accelerated Segment Test), was selected to extract the feature points. The matching point pairs were then detected between the images, the outliers were eliminated, and geometric transformation was performed. The appropriate window size was searched and set to one-tenth of the image width. The images that were acquired by a two-camera system, a camera with five imaging sensors, and a camera with replaceable filters mounted on a manned aircraft, an unmanned aerial vehicle, and a ground-based platform, respectively, were used to evaluate the performance of the proposed method. The image analysis results showed that, through the appropriate window selection and histogram specification, the number of correctly matched point pairs had increased by 11.30 times, and that the correct matching rate had increased by 36%, compared with the results based on FAST alone. The root mean square error (RMSE) in the x and y directions was generally within 0.5 pixels. In comparison with the binary robust invariant scalable keypoints (BRISK), curvature scale space (CSS), Harris, speed up robust features (SURF), and commercial software ERDAS and ENVI, this method resulted in larger numbers of correct matching pairs and smaller, more consistent RMSE. Furthermore, it was not necessary to choose any tie control points manually before registration. The results from this study indicate that the proposed method can be effective for registering optical multimodal remote sensing images that have been captured with different imaging sensors.<\/jats:p>","DOI":"10.3390\/rs10050663","type":"journal-article","created":{"date-parts":[[2018,4,25]],"date-time":"2018-04-25T03:22:45Z","timestamp":1524626565000},"page":"663","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Registration for Optical Multimodal Remote Sensing Images Based on FAST Detection, Window Selection, and Histogram Specification"],"prefix":"10.3390","volume":"10","author":[{"given":"Xiaoyang","family":"Zhao","sequence":"first","affiliation":[{"name":"College of Resource and Environment, Huazhong Agricultural University, 1 Shizishan Street, Wuhan 430070, China"},{"name":"Key Laboratory of Arable Land Conservation (Middle and Lower Reaches of Yangtse River), Ministry of Agriculture, 1 Shizishan Street, Wuhan 430070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9890-3598","authenticated-orcid":false,"given":"Jian","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Resource and Environment, Huazhong Agricultural University, 1 Shizishan Street, Wuhan 430070, China"},{"name":"Key Laboratory of Arable Land Conservation (Middle and Lower Reaches of Yangtse River), Ministry of Agriculture, 1 Shizishan Street, Wuhan 430070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenghai","family":"Yang","sequence":"additional","affiliation":[{"name":"USDA-Agricultural Research Service, Aerial Application Technology Research Unit, 3103 F &amp; B Road, College Station, TX 77845, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huaibo","family":"Song","sequence":"additional","affiliation":[{"name":"College of Mechanical and Electronic Engineering, Northwest A&amp;F University, 22 Xinong Road, Yangling 712100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yeyin","family":"Shi","sequence":"additional","affiliation":[{"name":"Department of Biological Systems Engineering, University of Nebraska-Lincoln, 3605 Fair Street, Lincoln, NE 68583, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xingen","family":"Zhou","sequence":"additional","affiliation":[{"name":"Texas A&amp;M AgriLife Research and Extension Center, Beaumont, TX 77713, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongyan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Anhui Engineering Laboratory of Agro-Ecological Big Data, Anhui University, Hefei 230601, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guozhong","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Engineering, Huazhong Agricultural University, 1 Shizishan Street, Wuhan 430070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,4,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Aicardi, I., Nex, F., Gerke, M., and Lingua, A. (2016). An image-based approach for the co-registration of multi-temporal uav image datasets. Remote Sens., 8.","DOI":"10.3390\/rs8090779"},{"key":"ref_2","unstructured":"Pritt, M., and Gribbons, M.A. (2014). Automated Registration of Synthetic Aperture Radar Imagery with High Resolution Digital Elevation Models. (No. 8,842,036), U.S. Patent."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1875","DOI":"10.3390\/rs5041875","article-title":"Generating virtual images from oblique frames","volume":"5","author":"Tommaselli","year":"2013","journal-title":"Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1313","DOI":"10.1364\/JOSAA.33.001313","article-title":"Nonrigid registration of remote sensing images via sparse and dense feature matching","volume":"33","author":"Chen","year":"2016","journal-title":"J. Opt. Soc. Am. A"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1736","DOI":"10.3390\/rs70201736","article-title":"Time series analysis of landslide dynamics using an unmanned aerial vehicle (UAV)","volume":"7","author":"Turner","year":"2015","journal-title":"Remote Sens."},{"key":"ref_6","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_7","doi-asserted-by":"crossref","unstructured":"Grant, B.G. (2017, January 1). UAV imagery analysis: Challenges and opportunities. Proceedings of the Long-Range Imaging II, Anaheim, CA, USA.","DOI":"10.1117\/12.2264138"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Zhang, J., Yang, C., Song, H., Hoffmann, W., Zhang, D., and Zhang, G. (2016). Evaluation of an airborne remote sensing platform consisting of two consumer-grade cameras for crop identification. Remote Sens., 8.","DOI":"10.3390\/rs8030257"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"393","DOI":"10.5194\/isprsarchives-XXXIX-B1-393-2012","article-title":"Sensor correction and radiometric calibration of a 6-band multispectral imaging sensor for uav remote sensing","volume":"39-B1","author":"Kelcey","year":"2012","journal-title":"Int. Arch. Photogramm. Remote. Sens. Spat. Inf. Sci."},{"key":"ref_10","unstructured":"Dehaan, R. (2015). Evaluation of Unmanned Aerial Vehicle (UAV)-Derived Imagery for the Detection of Wild Radish in Wheat, Charles Sturt University."},{"key":"ref_11","first-page":"618","article-title":"Spectral characterization of COTS RGB cameras using a linear variable edge filter","volume":"8660","author":"Bongiorno","year":"2013","journal-title":"Korean J. Chem. Eng."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"McKee, M. (2017, January 8). The remote sensing data from your UAV probably isn\u2019t scientific, but it should be!. Proceedings of the Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping II, Anaheim, CA, USA.","DOI":"10.1117\/12.2267722"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1016\/S0262-8856(03)00137-9","article-title":"Image registration methods: A survey","volume":"21","author":"Zitova","year":"2003","journal-title":"Image Vis. Comput."},{"key":"ref_14","first-page":"130","article-title":"Area based image matching methods\u2014A survey","volume":"2","author":"Joglekar","year":"2012","journal-title":"Int. J. Emerg. Technol. Adv. Eng."},{"key":"ref_15","unstructured":"Moigne, J.L., Netanyahu, N.S., and Eastman, R.D. (2011). Image Registration for Remote Sensing, Cambridge University Press."},{"key":"ref_16","unstructured":"Hong, G., and Zhang, Y. (2007, January 23\u201328). Combination of feature-based and area-based image registration technique for high resolution remote sensing image. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Barcelona, Spain."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2572","DOI":"10.3390\/rs6032572","article-title":"Robust automated image co-registration of optical multi-sensor time series data: Database generation for multi-temporal landslide detection","volume":"6","author":"Behling","year":"2014","journal-title":"Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1111\/j.0031-868X.2003.00254.x","article-title":"Line-based modified iterated Hough transform for automatic registration of multi-source imagery","volume":"19","author":"Habib","year":"2004","journal-title":"Photogramm. Rec."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"414","DOI":"10.1109\/LGRS.2008.916646","article-title":"Automated image registration for hydrologic change detection in the lake-rich Arctic","volume":"5","author":"Sheng","year":"2008","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3908","DOI":"10.1109\/TGRS.2008.2000636","article-title":"Automated image registration based on pseudoinvariant metrics of dynamic land-surface features","volume":"46","author":"Shah","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_21","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_22","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/0262-8856(88)90003-0","article-title":"3D positional integration from image sequences","volume":"6","author":"Harris","year":"1988","journal-title":"Image Vis. Comput."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.cviu.2007.09.014","article-title":"Speeded-up robust features (SURF)","volume":"110","author":"Bay","year":"2008","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_24","unstructured":"Rosten, E., and Drummond, T. (, January May). Machine learning for high-speed corner detection. Proceedings of the European Conference on Computer Vision, Berlin\/Heidelberg, Germany."},{"key":"ref_25","first-page":"1049","article-title":"Registration techniques for multisensor remotely sensed images","volume":"62","author":"Fonseca","year":"1996","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1145\/146370.146374","article-title":"A survey of image registration techniques","volume":"24","author":"Brown","year":"1992","journal-title":"Acm Comput. Surv."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Lowe, D.G. (1999, January 20\u201327). Object recognition from local scale-invariant features. Proceedings of the Seventh IEEE International Conference on Computer Vision, Kerkyra, Greece.","DOI":"10.1109\/ICCV.1999.790410"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1023\/A:1008045108935","article-title":"Feature detection with automatic scale selection","volume":"30","author":"Lindeberg","year":"1998","journal-title":"Int. J. Comput. Vis."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Bay, H., Tuytelaars, T., and Gool, L.V. (2006, January 7\u201313). SURF: Speeded up robust features. Proceedings of the European Conference on Computer Vision, Graz, Austria.","DOI":"10.1007\/11744023_32"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1376","DOI":"10.1109\/34.735812","article-title":"Robust image corner detection through curvature scale space","volume":"20","author":"Mokhtarian","year":"1998","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_31","unstructured":"Harris, C. (September, January 31). A combined corner and edge detector. Proceedings of the Fourth Alvey Vision Conference, Manchester, UK."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Rosten, E., and Drummond, T. (2005, January 17\u201321). Fusing points and lines for high performance tracking. Proceedings of the Tenth IEEE International Conference on Computer Vision, Beijing, China.","DOI":"10.1109\/ICCV.2005.104"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1007\/978-3-642-38267-3_15","article-title":"A fast algorithm for exact histogram specification. Simple extension to colour images","volume":"7893","author":"Nikolova","year":"2013","journal-title":"Lect. Notes Comput. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1006\/cviu.1999.0832","article-title":"MLESAC: A new robust estimator with application to estimating image geometry","volume":"78","author":"Torr","year":"2000","journal-title":"Comput. Vis. Image Underst."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2829","DOI":"10.1109\/TGRS.2010.2042813","article-title":"Fully automatic subpixel image registration of multiangle chris\/proba data","volume":"48","author":"Ma","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_36","first-page":"233","article-title":"Different source image registration method based on texture common factor","volume":"42","author":"Yang","year":"2016","journal-title":"Comput. Eng."},{"key":"ref_37","unstructured":"Hexagon Geospatial (2018, April 09). ERDAS IMAGINE Help. Available online: https:\/\/hexagongeospatial.fluidtopics.net\/reader\/P7L4c0T_d3papuwS98oGQ\/A6cPYHL_ydRnsJNL9JttFA."},{"key":"ref_38","unstructured":"Harris Geospatial Solutions (2018, April 09). Docs Center. Using ENVI. Automatic Image to Image Registration. Available online: http:\/\/www.harrisgeospatial.com\/docs\/RegistrationImageToImage.html."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/5\/663\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T15:01:59Z","timestamp":1760194919000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/5\/663"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,4,24]]},"references-count":38,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2018,5]]}},"alternative-id":["rs10050663"],"URL":"https:\/\/doi.org\/10.3390\/rs10050663","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2018,4,24]]}}}