计算机应用研究
計算機應用研究
계산궤응용연구
APPLICATION RESEARCH OF COMPUTERS
2015年
9期
2862-2865
,共4页
无人机遥感影像%三维重构%影像拼接%姿态估计%捆集调整
無人機遙感影像%三維重構%影像拼接%姿態估計%捆集調整
무인궤요감영상%삼유중구%영상병접%자태고계%곤집조정
UAV remote sensing images%3D reconstruction%image mosaic%pose estimation%bundle adjustment
针对无人机遥感影像三维重建需求,提出了基于MPB(mosaic-pose-bundle)的三维重建方法,将三维重建过程分为影像拼接、姿态估计、捆集调整三个步骤。影像拼接是将所有遥感影像配准到一个基准平面,建立地形的平面模型;姿态估计则根据平面模型解算出相机的外参数,完成相机的概率定向;捆集调整则是对定向参数和平面坐标进行非线性优化,完成地形的稀疏三维重建,并在此基础上重建场景的PMVS点云,进行表面重建及纹理映射,完成地形的实景真三维重建。依据上述思路,开发了一套基于无人机遥感影像的三维重建系统,通过对不同地形的遥感影像进行测试,验证了方法的正确性及稳定性,相对于传统的三维重建系统更加高效,为遥感影像的三维重建提供一种高效、稳健的新方法。
針對無人機遙感影像三維重建需求,提齣瞭基于MPB(mosaic-pose-bundle)的三維重建方法,將三維重建過程分為影像拼接、姿態估計、捆集調整三箇步驟。影像拼接是將所有遙感影像配準到一箇基準平麵,建立地形的平麵模型;姿態估計則根據平麵模型解算齣相機的外參數,完成相機的概率定嚮;捆集調整則是對定嚮參數和平麵坐標進行非線性優化,完成地形的稀疏三維重建,併在此基礎上重建場景的PMVS點雲,進行錶麵重建及紋理映射,完成地形的實景真三維重建。依據上述思路,開髮瞭一套基于無人機遙感影像的三維重建繫統,通過對不同地形的遙感影像進行測試,驗證瞭方法的正確性及穩定性,相對于傳統的三維重建繫統更加高效,為遙感影像的三維重建提供一種高效、穩健的新方法。
침대무인궤요감영상삼유중건수구,제출료기우MPB(mosaic-pose-bundle)적삼유중건방법,장삼유중건과정분위영상병접、자태고계、곤집조정삼개보취。영상병접시장소유요감영상배준도일개기준평면,건입지형적평면모형;자태고계칙근거평면모형해산출상궤적외삼수,완성상궤적개솔정향;곤집조정칙시대정향삼수화평면좌표진행비선성우화,완성지형적희소삼유중건,병재차기출상중건장경적PMVS점운,진행표면중건급문리영사,완성지형적실경진삼유중건。의거상술사로,개발료일투기우무인궤요감영상적삼유중건계통,통과대불동지형적요감영상진행측시,험증료방법적정학성급은정성,상대우전통적삼유중건계통경가고효,위요감영상적삼유중건제공일충고효、은건적신방법。
This paper investigated the 3D reconstruction of the UAV remote sensing images,and prpopsed a novel reconstruc-tion framework(MPB)which explicitly decomposed the reconstruction task into image mosaic,camera pose estimation and bundle adjustment.Image mosaic means that all remote sensing images would be registrated into a plane to establish the plane model of terrain,then it estimated the camera pose from the plane model of terrain,bundle adjustment the camera poses and the terrain coordinates to complete the terrain 3D sparse reconstruction.This paper got the dense points based on the PMVS algo-rithm,and did a surface reconstruction and texture mapping to complete the 3D reconstruction.Based on the above ideas,it de-velopped a UAV remote sensing image 3D reconstruction system,and conducted extensive testing.The results show that the sys-tem can improve the reconstruction efficiency greatly,providing a fast and efficient approach for 3D reconstruction of remote sensing data.