本文關(guān)鍵詞： 航空影像 機(jī)載LiDAR點(diǎn)云 自動配準(zhǔn) 精度分析　出處：《蘭州交通大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：目前為止，航空攝影測量的解析理論已經(jīng)基本完備，是測繪生產(chǎn)單位制作地圖的重要手段之一，經(jīng)過航空攝影測量一系列處理，可以得到影像的方位元素，還原影像拍攝的位置和姿態(tài)，進(jìn)而生產(chǎn)數(shù)字高程模型（Digital Elevation Model，DEM），數(shù)字線劃地圖(Digital Line Graphic，DLG)，數(shù)字正射影像圖（Digital Orthophoto Map，DOM）和三維城市模型等。機(jī)載LiDAR（Light Detection And Ranging，機(jī)載激光掃描）系統(tǒng)可以快速獲取大面積地表離散點(diǎn)三維坐標(biāo)數(shù)據(jù)和其他信息。LiDAR點(diǎn)云密度越來越大，精度也越來越高，其應(yīng)用推廣很有可能引起測量技術(shù)的又一次革命。然而，雖然激光掃描能夠直接獲得目標(biāo)的三維空間信息，地物分類信息也比較容易獲得，但是，它卻難以表達(dá)目標(biāo)表面的紋理信息。如果僅僅利用數(shù)字影像恢復(fù)目標(biāo)的幾何信息需要經(jīng)過復(fù)雜的數(shù)據(jù)處理流程，涉及到影像特征提取、影像匹配、影像交會、構(gòu)網(wǎng)及紋理映射等關(guān)鍵問題。激光掃描數(shù)據(jù)和航空影像數(shù)據(jù)，在信息的表達(dá)、恢復(fù)目標(biāo)的三維信息處理過程中，各有優(yōu)勢和不足，可以互為補(bǔ)充。一方面，影像數(shù)據(jù)可以彌補(bǔ)LiDAR點(diǎn)云數(shù)據(jù)紋理表現(xiàn)上的缺陷；另一方面，利用LiDAR點(diǎn)云數(shù)據(jù)也可以提高影像恢復(fù)目標(biāo)三維幾何信息的效率。 本文以傳統(tǒng)的空中三角測量為基礎(chǔ)，按照POS（Positionand OrientationSystem，定位定向系統(tǒng)）輔助空三的作業(yè)流程進(jìn)行研究。首先，研究針對帶POS的航空影像，在LiDAR點(diǎn)云數(shù)據(jù)的輔助下進(jìn)行空三連接點(diǎn)自動提�。黄浯�，為了獲取良好的像控點(diǎn)，參照像控點(diǎn)的布設(shè)方案，選取測區(qū)局部區(qū)域進(jìn)行基于物方約束的多視影像匹配，得到匹配點(diǎn)云；然后，研究利用ICP算法將匹配點(diǎn)云與機(jī)載LiDAR點(diǎn)云配準(zhǔn)，并篩選配準(zhǔn)點(diǎn)作為像控點(diǎn)，進(jìn)行平差，經(jīng)過迭代解算影像在LiDAR坐標(biāo)框架下的外方位元素，實(shí)現(xiàn)航空影像與機(jī)載LiDAR數(shù)據(jù)的自動配準(zhǔn)；最后，對配準(zhǔn)的精度進(jìn)行評價，方法是利用專業(yè)LiDAR觀測軟件提取檢查點(diǎn)三維坐標(biāo)，同時在立體觀測模式下精確地量測影像上同名點(diǎn)的三維坐標(biāo)，應(yīng)用點(diǎn)位中誤差的思想分析自動配準(zhǔn)精度。 在對機(jī)載LiDAR點(diǎn)云數(shù)據(jù)和航空影像的自動配準(zhǔn)結(jié)果進(jìn)行精度評價的過程中，涉及的重點(diǎn)與創(chuàng)新點(diǎn)包括以下幾方面： （1）利用POS和LiDAR數(shù)據(jù)在物方約束下進(jìn)行航空影像空三轉(zhuǎn)點(diǎn)； （2）基于多目視覺在POS和LiDAR數(shù)據(jù)物方約束下的高精度影像匹配，獲取局部區(qū)域密集匹配點(diǎn)云，將航空影像與LiDAR點(diǎn)云的配準(zhǔn)問題，轉(zhuǎn)化為影像匹配點(diǎn)云與LiDAR點(diǎn)云的配準(zhǔn)問題； （3）應(yīng)用ICP（Iterative Closest Point，迭代最近點(diǎn)）算法進(jìn)行影像匹配點(diǎn)云與LiDAR點(diǎn)云的配準(zhǔn)； （4）航空影像控制片選取，配準(zhǔn)精度評定； （5）創(chuàng)新性地提出利用良好配準(zhǔn)點(diǎn)作為航空影像的像控點(diǎn)，代替像控點(diǎn)的人工選取，并且提高了像控點(diǎn)的量測精度，以及影像方位元素的解算精度。 本文研究的內(nèi)容，能夠較好地解決航空影像與機(jī)載LiDAR點(diǎn)云數(shù)據(jù)的自動配準(zhǔn)問題，并且通過評判自動配準(zhǔn)精度保證了自動配準(zhǔn)的質(zhì)量，是航空影像數(shù)據(jù)與機(jī)載LiDAR數(shù)據(jù)集成的關(guān)鍵技術(shù)之一，有利于推動航空攝影測量和機(jī)載LiDAR技術(shù)的更廣泛應(yīng)用。將本文研究的內(nèi)容集成到機(jī)載LiDAR數(shù)據(jù)處理軟件（如：LiDARStation.Pro）和航空影像數(shù)據(jù)處理軟件（如：PixelGrid）等中去，，在應(yīng)用到測繪生產(chǎn)單位后，能夠提高相關(guān)數(shù)據(jù)的處理效率，同時取得一定的經(jīng)濟(jì)效益。 隨著經(jīng)濟(jì)技術(shù)的發(fā)展，社會各界對測繪提出了更高的要求，最大限度地發(fā)揮航空攝影和機(jī)載LiDAR的技術(shù)優(yōu)勢，成為一個測繪相關(guān)部門的新需求。本文的研究內(nèi)容是航空攝影測量數(shù)據(jù)與機(jī)載LiDAR數(shù)據(jù)集成的前提，為進(jìn)一步獲取更高質(zhì)量的數(shù)字產(chǎn)品，特別是真正射影像和三維城市建模，提供理論基礎(chǔ)和技術(shù)參考。
[Abstract]:So far, analytical theory of aerial photogrammetry has been basically completed, is one of the important means of production of Surveying and mapping production unit map, after a series of aerial photogrammetry processing, image orientation elements can get the position and attitude of restoring the image shooting, and the production of digital elevation model (Digital Elevation Model, DEM), digital line map (Digital Line Graphic, DLG), digital orthophoto map (Digital Orthophoto Map, DOM) and the 3D city model. LiDAR (Light Detection And Ranging airborne, airborne laser scanning) system can quickly obtain cloud density and large area surface discrete three-dimensional coordinate data and other information of.LiDAR is larger, and precision the higher the application is likely to cause a revolution in measurement technology. However, although the three-dimensional spatial information of laser scanning can directly obtain the goal, feature points Such information is also relatively easy to obtain, but it is difficult to express the texture information of the target surface. If only the recovery target using digital image geometric information requires complex data processing, related to image feature extraction, image matching, image intersection, key problems of triangulation and texture mapping. The laser scanning data and aerial images the data in the information expression, 3D information processing recovery goals, each has advantages and disadvantages, can complement each other. On the one hand, the image data can make up for the defects of LiDAR point cloud data on the performance of the texture; on the other hand, the utilization efficiency of LiDAR point cloud data can also improve the image restoration target 3D geometric information.
This paper is based on the traditional aerial triangulation, according to the POS (Positionand OrientationSystem, positioning and orientation system) of auxiliary operation process three. First, research on aerial images with POS, empty three connection points in the LiDAR point cloud data automatically extracted; secondly, in order to obtain good control reference point, the layout scheme of image control points, selected test area local region object constraint in multi view image matching based on match point cloud; then, ICP algorithm using the matching point cloud and airborne LiDAR point cloud registration, screening and registration points as control points as, after adjustment, the exterior orientation iterative image elements in LiDAR coordinate frame, realize the automatic registration of aerial image and airborne LiDAR data; finally, to evaluate the accuracy of registration. The method is the use of professional LiDAR software to extract the observation check point three At the same time in the dimensional coordinates, three-dimensional observation mode accurately measured image points the 3D coordinates analysis of automatic registration accuracy by using the point position error of thought.
In the process of accuracy evaluation of airborne LiDAR point cloud data and automatic registration results of aerial images, the key points and innovation points include the following aspects:
(1) using POS and LiDAR data to carry out aerial image empty three turning points under the constraint of the object square;
(2) based on the high-precision image matching under the constraint of POS and LiDAR data objects, we get the local area dense matching point cloud based on multi view vision, and transform the registration problem between the aerial image and LiDAR point cloud into the registration problem of image matching point cloud and LiDAR point cloud.
(3) ICP (Iterative Closest Point, iterative nearest point) algorithm is applied to registration of image matching point cloud and LiDAR point cloud.
(4) the selection of aerial image control film and the evaluation of registration accuracy;
(5) innovatively put forward the use of good registration points as the image control points of aerial images instead of manual selection of image points, and improve the accuracy of image control points and the accuracy of image orientation elements.
The content of this paper, can effectively solve the problem of automatic registration of aerial image and airborne LiDAR point cloud data, automatic registration of the quality assurance and evaluation through the automatic registration accuracy is one of the key technologies of the integration of aerial image data and airborne LiDAR data, is beneficial to promote more widely application of aerial photogrammetry and airborne LiDAR technology. The content of this paper will be integrated into the software of airborne LiDAR data processing (such as LiDARStation.Pro) and aerial image data processing software (such as PixelGrid) and go to mapping units after application can improve the processing efficiency of the relevant data, and obtain certain economic benefits.
With the development of economy and technology, society has put forward higher requirements for surveying and mapping, to maximize the advantages of aerial photography and airborne LiDAR, become a new demand for the relevant departments of Surveying and mapping. The research content of this paper is the premise of aerial photogrammetry data and airborne LiDAR data integration, to further obtain higher digital products the quality, especially the real projective image and 3D city modeling, provide theoretical basis and technical reference.

【學(xué)位授予單位】：蘭州交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：P231;P28

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本文編號：1519058