【摘要】：目的像方無人機影像多視匹配方法忽視了影像之間的幾何關(guān)系,而以MVLL(multi-view vertical line locus)為代表的物方多視匹配方法缺乏對地形之間相互約束的考慮。為此構(gòu)建一種融合兩類多視匹配方法優(yōu)點的無人機影像物方多視匹配算法。方法在MVLL匹配結(jié)構(gòu)的基礎(chǔ)上添加半全局匹配的相容性約束,不僅繼承了原半全局算法對有弱紋理區(qū)域匹配效果好和物體邊緣突出的優(yōu)點,而且擺脫了需制作核線影像的繁瑣過程;采用物方窗口SNCC(summed normalized cross correlation)一致性匹配測度計算方法,有效降低攝影角度和遮擋對匹配結(jié)果的影響;采用金字塔分層的策略以提高匹配的速度和可靠性。結(jié)果選取自主研制的旋翼無人機三軸穩(wěn)定平臺獲取了高分辨率無人機影像作為實驗數(shù)據(jù),從匹配效果、新匹配測度性能和匹配精度3個方面對算法進行了測試實驗。本文算法整體匹配效果良好,物方窗口SNCC一致性匹配測度可有效消除匹配測度中的粗差,經(jīng)過測定本文匹配算法生成的點云數(shù)據(jù)的高程精度為0.049 m,即約為1個GSD(ground space resolution)對應(yīng)的地面大小。結(jié)論本文算法充分利用了無人機影像的多視信息進行匹配計算,具有匹配效果好、魯棒性強和匹配精度高的優(yōu)勢。
[Abstract]:Objective the image multi-view matching method of image square UAV neglects the geometric relationship between images, while the object multi-view matching method represented by multi-view vertical line locus) lacks the consideration of the mutual constraint between terrain. In this paper, an object-square multi-view matching algorithm for UAV images is proposed, which combines the advantages of two kinds of multi-view matching methods. Based on the MVLL matching structure, the compatibility constraint of semi-global matching is added, which not only inherits the advantages of the original semi-global algorithm, but also has the advantages of good matching effect on weakly textured regions and prominent edges of objects. Moreover, it gets rid of the tedious process of making core line image, adopts the method of object window SNCC (summed normalized cross correlation) consistency matching measure, effectively reduces the influence of camera angle and occlusion on the matching result. Pyramid stratification strategy is adopted to improve the speed and reliability of matching. Results High-resolution UAV images were obtained from a self-developed three-axis stabilized platform for rotors. The algorithm was tested from three aspects: matching effect, performance of new matching measure and matching accuracy. The overall matching effect of this algorithm is good, and the coarse error in the matching measure can be effectively eliminated by the object window SNCC consistency matching measure. The height accuracy of the point cloud data generated by the matching algorithm in this paper is 0.049 m, that is, the ground size corresponding to about 1 GSD (ground space resolution). Conclusion the algorithm makes full use of the multi-view information of UAV images and has the advantages of good matching effect, strong robustness and high matching accuracy.
【作者單位】： 信息工程大學(xué);地理信息工程國家重點實驗室;航空遙感技術(shù)國家測繪地理信息局重點實驗室;
【基金】：國家自然科學(xué)基金項目(41501482) 地理信息工程國家重點實驗室開放研究基金項目(SKLGIE 2015-M-3-6和SKLGIE 2014-M-3-1) 航空遙感技術(shù)國家測繪地理信息局重點實驗室開放基金項目(2014B02)~~
【分類號】：P231

【相似文獻】

相關(guān)期刊論文 前6條

1 韓心志;航天遙感多光譜掃描儀物方擺鏡的高速攝影測試[J];高速攝影與光子學(xué);1987年03期

2 游傳金;Topocart-D型儀y對稱性誤差的分析與校正[J];測繪通報;1990年04期

3 張祖勛,張劍清,胡翔云;基于物方空間幾何約束最小二乘匹配的建筑物半自動提取方法[J];武漢大學(xué)學(xué)報(信息科學(xué)版);2001年04期

4 王樹根,李賓,王海濤,仲思東;基于車載CCD影像的物方幾何參數(shù)量算[J];測繪信息與工程;2001年01期

5 侯文廣;商浩亮;馮文灝;;二維控制場建立中的關(guān)鍵技術(shù)研究[J];測繪科學(xué);2006年02期

6 ;[J];;年期

相關(guān)會議論文 前1條

1 王樹根;李賓;王海濤;仲思東;;基于車載CCD影像的物方幾何參數(shù)量算[A];新世紀 新機遇 新挑戰(zhàn)——知識創(chuàng)新和高新技術(shù)產(chǎn)業(yè)發(fā)展（上冊）[C];2001年

相關(guān)博士學(xué)位論文 前1條

1 樊仲謀;攝影測樹原理與技術(shù)方法研究[D];北京林業(yè)大學(xué);2015年

相關(guān)碩士學(xué)位論文 前1條

1 齊潤冰;物方三角網(wǎng)約束的多視影像密集匹配[D];遼寧工程技術(shù)大學(xué);2015年

，

本文編號：2121389