本文選題：LiDAR + 點(diǎn)云　； 參考：《西安電子科技大學(xué)》2014年碩士論文

【摘要】：機(jī)載激光雷達(dá)技術(shù)(Light Detection And Ranging,LiDAR)結(jié)合了航空影像技術(shù)與遙感技術(shù)的優(yōu)點(diǎn),這種創(chuàng)新性的思路為地形探測帶來了一次重大的改革。機(jī)載LiDAR技術(shù)可以獲取高精度海量的離散點(diǎn)云數(shù)據(jù),并且可以根據(jù)需求調(diào)整點(diǎn)云的密度,使得測量技術(shù)更加智能化,實(shí)用化。近年來,隨著城市建設(shè)的高速發(fā)展,如何精確快速獲取城市地形、建筑物分布、以及各類地物的邊緣就顯得特別重要。目前,通過LiDAR數(shù)據(jù)進(jìn)行城市三維重建越來越受到人們的重視,而建筑物的提取是其關(guān)鍵的一步。本文根據(jù)不同地形和地物的外部特征,對LiDAR數(shù)據(jù)的邊緣檢測以及建筑物提取進(jìn)行了研究。主要內(nèi)容包括以下兩部分:1.針對傳統(tǒng)的邊緣檢測方法梯度計(jì)算量大的問題,提出了一種基于不規(guī)則三角網(wǎng)(Triangulated Irregular Network,TIN)法向量的LiDAR點(diǎn)云數(shù)據(jù)的邊緣檢測新方法。首先構(gòu)建不規(guī)則三角網(wǎng),計(jì)算每個(gè)三角形的法向量以及每個(gè)法向量與水平面的夾角,通過跟夾角閾值比較,提取出邊緣三角形,將邊緣三角形的最高點(diǎn)作為邊緣點(diǎn)。夾角閾值通過直方圖統(tǒng)計(jì)得到。實(shí)驗(yàn)結(jié)果表明,該算法能夠較好的提取LiDAR點(diǎn)云數(shù)據(jù)的邊緣點(diǎn)。本文對河流區(qū)域出現(xiàn)的數(shù)據(jù)空白進(jìn)行插值,得到了較好的河流邊緣。2.針對傳統(tǒng)建筑物檢測數(shù)據(jù)點(diǎn)不完整的問題,提出了一種通過LiDAR數(shù)據(jù)輪廓線提取建筑物的新方法。首先對濾波后的點(diǎn)云數(shù)據(jù)構(gòu)造不規(guī)則三角網(wǎng),根據(jù)每個(gè)點(diǎn)臨近的三角形法向量夾角判斷三角面共面,檢測出初始建筑物點(diǎn)。然后利用邊長閾值把三角網(wǎng)分離成建筑物內(nèi)部三角網(wǎng)和邊界三角網(wǎng),提取邊界三角網(wǎng)中的較短邊拼接得到建筑物輪廓。最后通過判斷每個(gè)點(diǎn)是否在建筑物輪廓內(nèi)部,提取出輪廓線內(nèi)部的建筑物點(diǎn)。實(shí)驗(yàn)結(jié)果表明,該算法能夠較好的提取Li DAR數(shù)據(jù)的建筑物點(diǎn),并準(zhǔn)確地得到了建筑物的三維輪廓線。最終的建筑物提取正確率可以達(dá)到95%以上,完整率可以達(dá)到90%以上,達(dá)到了建筑物提取的精度要求。
[Abstract]:Airborne lidar technology combines the advantages of aerial image technology and remote sensing technology, which brings an important innovation for terrain detection. Airborne LiDAR technology can obtain high accuracy and mass discrete point cloud data, and can adjust the density of point cloud according to the demand, making the measurement technology more intelligent and practical. In recent years, with the rapid development of urban construction, how to accurately and quickly obtain the urban topography, the distribution of buildings, and the edge of various features is particularly important. At present, people pay more and more attention to urban 3D reconstruction through LiDAR data, and the extraction of buildings is a key step. In this paper, the edge detection and building extraction of LiDAR data are studied according to the external features of different terrain and features. The main content includes the following two parts: 1. A new edge detection method for LiDAR point cloud data based on triangulated Irregular network normal vector is proposed to solve the problem of large gradient computation in traditional edge detection methods. Firstly, the irregular triangular network is constructed, the normal vectors of each triangle and the angle between each normal vector and the horizontal plane are calculated. By comparing with the angle threshold, the edge triangle is extracted and the highest point of the edge triangle is taken as the edge point. The angle threshold is obtained by histogram statistics. Experimental results show that the algorithm can extract the edge points of LiDAR point cloud data. In this paper, the data gaps in the river region are interpolated, and a better river edge. 2. 2. In order to solve the problem of incomplete data points in traditional building detection, a new method for extracting buildings by LiDAR data contours is proposed. Firstly, irregular triangulation is constructed for the filtered point cloud data, and the initial building point is detected according to the angle of the triangle normal vector near each point. Then the triangulation network is separated into the building inner triangular network and the boundary triangulation network by using the edge length threshold, and the building contour is obtained by extracting the shorter edges from the boundary triangulation network. Finally, by judging whether each point is inside the building contour, the building points inside the contour line are extracted. The experimental results show that the algorithm can extract the building points of Li DAR data and get the 3D contour of the building accurately. The final correct rate of building extraction can reach more than 95%, and the complete rate can reach more than 90%, which meets the precision requirement of building extraction.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TU198;TN958.98

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本文編號：1790978