{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,29]],"date-time":"2025-12-29T11:09:05Z","timestamp":1767006545115,"version":"build-2065373602"},"reference-count":56,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2019,1,10]],"date-time":"2019-01-10T00:00:00Z","timestamp":1547078400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41431179","41601365"],"award-info":[{"award-number":["41431179","41601365"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"GuangXi Key Laboratory for Spatial Information and Geomatics Program","award":["17-259-16-09"],"award-info":[{"award-number":["17-259-16-09"]}]},{"name":"GuangXi innovative Development Grand under Grant","award":["2018AA13005"],"award-info":[{"award-number":["2018AA13005"]}]},{"name":"GuangXi Key Research and development Program of China under Grant number","award":["2016YFB502501"],"award-info":[{"award-number":["2016YFB502501"]}]},{"name":"the State Oceanic Administration under Grant number","award":["[2014]#58"],"award-info":[{"award-number":["[2014]#58"]}]},{"DOI":"10.13039\/501100004607","name":"GuangXi Natural Science Foundation","doi-asserted-by":"publisher","award":["2015GXNSFDA139032"],"award-info":[{"award-number":["2015GXNSFDA139032"]}],"id":[{"id":"10.13039\/501100004607","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangxi Key Laboratory of Spatial Information and Geomatics Program","award":["15-140-07-01 and 16-380-25-12"],"award-info":[{"award-number":["15-140-07-01 and 16-380-25-12"]}]},{"name":"GuangXi innovative Development Grand Grant","award":["GuiKe AA18118038"],"award-info":[{"award-number":["GuiKe AA18118038"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>For real-time monitoring of natural disasters, such as fire, volcano, flood, landslide, and coastal inundation, highly-accurate georeferenced remotely sensed imagery is needed. Georeferenced imagery can be fused with geographic spatial data sets to provide geographic coordinates and positing for regions of interest. This paper proposes an on-board georeferencing method for remotely sensed imagery, which contains five modules: input data, coordinate transformation, bilinear interpolation, and output data. The experimental results demonstrate multiple benefits of the proposed method: (1) the computation speed using the proposed algorithm is 8 times faster than that using PC computer; (2) the resources of the field programmable gate array (FPGA) can meet the requirements of design. In the coordinate transformation scheme, 250,656 LUTs, 499,268 registers, and 388 DSP48s are used. Furthermore, 27,218 LUTs, 45,823 registers, 456 RAM\/FIFO, and 267 DSP48s are used in the bilinear interpolation module; (3) the values of root mean square errors (RMSEs) are less than one pixel, and the other statistics, such as maximum error, minimum error, and mean error are less than one pixel; (4) the gray values of the georeferenced image when implemented using FPGA have the same accuracy as those implemented using MATLAB and Visual studio (C++), and have a very close accuracy implemented using ENVI software; and (5) the on-chip power consumption is 0.659 W. Therefore, it can be concluded that the proposed georeferencing method implemented using FPGA with second-order polynomial model and bilinear interpolation algorithm can achieve real-time geographic referencing for remotely sensed imagery.<\/jats:p>","DOI":"10.3390\/rs11020124","type":"journal-article","created":{"date-parts":[[2019,1,11]],"date-time":"2019-01-11T04:10:16Z","timestamp":1547179816000},"page":"124","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["On-Board Georeferencing Using FPGA-Based Optimized Second-Order Polynomial Equation"],"prefix":"10.3390","volume":"11","author":[{"given":"Dequan","family":"Liu","sequence":"first","affiliation":[{"name":"School of Microelectronics, Tianjin University, Tianjin 300072, China"},{"name":"The Center for Remote Sensing, Tianjin University, Tianjin 300072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guoqing","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Microelectronics, Tianjin University, Tianjin 300072, China"},{"name":"School of Precision Instrument &amp; Opto-Electronics Engineering, Tianjin University, Tianjin 300072, China"},{"name":"The Center for Remote Sensing, Tianjin University, Tianjin 300072, China"},{"name":"GuangXi Key Laboratory for Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingjin","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Precision Instrument &amp; Opto-Electronics Engineering, Tianjin University, Tianjin 300072, China"},{"name":"The Center for Remote Sensing, Tianjin University, Tianjin 300072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rongting","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Precision Instrument &amp; Opto-Electronics Engineering, Tianjin University, Tianjin 300072, China"},{"name":"The Center for Remote Sensing, Tianjin University, Tianjin 300072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lei","family":"Shu","sequence":"additional","affiliation":[{"name":"School of Precision Instrument &amp; Opto-Electronics Engineering, Tianjin University, Tianjin 300072, China"},{"name":"The Center for Remote Sensing, Tianjin University, Tianjin 300072, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiang","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Microelectronics, Tianjin University, Tianjin 300072, China"},{"name":"GuangXi Key Laboratory for Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chun Sheng","family":"Xin","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, VA 23529, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,1,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1177\/0309133309339563","article-title":"A review of the status of satellite remote sensing and image processing techniques for mapping natural hazards and disasters","volume":"33","author":"Joyce","year":"2009","journal-title":"Prog. 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