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基于不規則三角網(wǎng)的遙感影像自動(dòng)配準系統設計
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廣州華商學(xué)院校內導師制科研基金資助項目:(No.2024HSDS12);


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    摘要:

    在遙感影像配準過(guò)程中,正射投影圖像會(huì )在矩形框頂點(diǎn)展開(kāi)排序。但由于地物場(chǎng)景形式的多樣性與影像采集傳感器平移、旋轉的多變性,影像特征區域之間呈現重疊覆蓋程度高、可區分性差的特點(diǎn),致使相同地物在不同影像中的位置存在偏移現象,這種幾何畸變導致遙感影像平均正確配準點(diǎn)率較低。為此,利用不規則三角網(wǎng)技術(shù),設計遙感影像自動(dòng)配準系統。改裝遙感影像采集器、角度傳感器、數據處理器,調整系統電源電路的連接方式,實(shí)現硬件系統的優(yōu)化設計,以保障數據庫數據的安全性和可靠性。利用遙感影像采集器光學(xué)原理,生成遙感影像,通過(guò)大氣校正、影像增強等步驟,保證生成遙感影像的生成質(zhì)量。采用Harris算子,提取遙感影像特征點(diǎn),以特征點(diǎn)為頂點(diǎn),利用Delaunay準則構建不規則三角網(wǎng),構建不規則三角網(wǎng),獲取遙感影像的分割線(xiàn),實(shí)現遙感影像的自動(dòng)分割,以更精確地糾正影像間的偏移問(wèn)題,解決幾何畸變對影像配準的正確配準率的影響。通過(guò)粗配準、精配準和誤配準剔除三個(gè)步驟,實(shí)現系統的遙感影像自動(dòng)配準功能。通過(guò)系統測試實(shí)驗得出結論:與傳統配準系統相比,優(yōu)化設計系統對低、高分辨率遙感影像的正確配準點(diǎn)率分別提高3.5%和1.9%,同時(shí)系統運行加速比明顯提升。

    Abstract:

    In the process of remote sensing image registration, the orthographic projection image will be expanded and sorted at the vertex of the rectangular box. However, due to the diversity of scene forms of ground objects and the variability of translation and rotation of image acquisition sensors, image feature regions present high overlapping coverage and poor differentiation, resulting in the position deviation of the same ground objects in different images, and this geometric distortion leads to a low average correct on-time allocation rate of remote sensing images. Therefore, an automatic remote sensing image registration system is designed by using triangulation irregular network technology. The remote sensing image collector, Angle sensor and data processor were modified, and the connection mode of the system power circuit was adjusted to realize the optimal design of the hardware system, so as to ensure the security and reliability of the database data. Using the optical principle of remote sensing image collector, the remote sensing image is generated, and the quality of the generated remote sensing image is guaranteed by the steps of atmospheric correction and image enhancement. The Harris operator is used to extract the feature points of remote sensing images, and the feature points are taken as the vertices. The triangulation irregularity network is constructed by the Delaunay criterion, and the division lines of remote sensing images are obtained to realize automatic segmentation of remote sensing images, so as to correct the deviation problem between images more accurately and solve the influence of geometric distortion on the correct registration rate of images. Through three steps of rough registration, fine registration and misregistration elimination, the automatic registration function of remote sensing image is realized. The experimental results show that compared with the traditional registration system, the correct registration rate of low and high resolution remote sensing images is improved by 3.5% and 1.9% respectively, and the acceleration ratio of the system is obviously improved.

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  • 收稿日期:2024-11-08
  • 最后修改日期:2024-12-16
  • 錄用日期:2024-12-19
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