發(fā)布時(shí)間：2018-04-16 02:17

  本文選題：高分辨率遙感影像 + 道路提取��； 參考：《南京理工大學(xué)》2014年碩士論文

【摘要】：道路信息是一種重要的基礎(chǔ)地理信息,從高分辨率遙感影像中提取道路可用于GIS數(shù)據(jù)的自動獲取和更新、目標(biāo)檢測、圖像匹配以及數(shù)字測圖等,是人工智能、計(jì)算機(jī)視覺、遙感科學(xué)以及攝影測量等領(lǐng)域的研究重點(diǎn)之一,具有極其重要的科學(xué)意義與實(shí)用價(jià)值。本文對高分辨率遙感影像道路的提取方法進(jìn)行了深入的研究,并結(jié)合高分辨率遙感影像中道路的特點(diǎn),對現(xiàn)有的道路提取方法做出了一些有益的改進(jìn)。 首先,實(shí)現(xiàn)了基于GIS信息與Ribbon Snake模型的高分辨率遙感影像道路的自動提取。利用GIS數(shù)據(jù)構(gòu)造的B樣條曲線作為道路的初始中心線,并根據(jù)道路區(qū)域的紋理特征設(shè)計(jì)區(qū)域能量函數(shù),通過自動調(diào)節(jié)各能量函數(shù)在總能量函數(shù)中所占的權(quán)重以及控制點(diǎn)的搜索范圍,實(shí)現(xiàn)了模型的分級演化。實(shí)驗(yàn)證明了該方法在初始輪廓曲線遠(yuǎn)離目標(biāo)位置情況下的有效性。 其次,改進(jìn)了path opening方法中的鄰接圖以提取曲率較大的道路,并將path opening與Ribbon Snake模型相結(jié)合,用于高分辨率遙感影像道路的自動精確提取。通過path opening操作獲取初始道路中心線,由Ribbon Snake模型進(jìn)行精確定位,得到準(zhǔn)確光滑的道路中心線以及兩條道路邊界,通過實(shí)驗(yàn)驗(yàn)證了該方法的可行性與有效性。 最后,提出了一種基于改進(jìn)path opening的有損道路自動提取新方法。該方法巧妙地將path opening算法中的最大路徑長度λ與區(qū)域的幾何特征相結(jié)合,建立了道路區(qū)域的判定準(zhǔn)則。通過實(shí)驗(yàn)對比分析,從實(shí)驗(yàn)效果和算法效率兩個(gè)角度證明了該方法的有效性和優(yōu)越性。
[Abstract]:Road information is an important basic geographic information. Road extraction from high-resolution remote sensing images can be used for automatic acquisition and updating of GIS data, target detection, image matching and digital mapping. It is artificial intelligence and computer vision.Remote sensing science and photogrammetry are of great scientific significance and practical value.In this paper, the road extraction methods in high-resolution remote sensing images are studied deeply, and some useful improvements are made to the existing road extraction methods combining with the characteristics of roads in high-resolution remote sensing images.Firstly, the road extraction of high resolution remote sensing image based on GIS information and Ribbon Snake model is realized.The B-spline curve constructed by GIS data is used as the initial centerline of the road, and the energy function of the region is designed according to the texture features of the road area.By automatically adjusting the weight of each energy function in the total energy function and the search range of the control point, the hierarchical evolution of the model is realized.The experimental results show that the method is effective when the initial contour is far from the target position.Secondly, the adjacent map in path opening method is improved to extract roads with large curvature, and the path opening and Ribbon Snake model are combined to extract the road automatically and accurately from high-resolution remote sensing images.The initial road centerline is obtained by path opening operation, and the accurate and smooth road centerline and two road boundaries are obtained by the Ribbon Snake model. The feasibility and effectiveness of the method are verified by experiments.Finally, a new method for automatic extraction of lossy roads based on improved path opening is proposed.The method skillfully combines the maximum path length 位 of path opening algorithm with the geometric characteristics of the region, and establishes the criterion of road region.The effectiveness and superiority of this method are proved from two aspects of experimental effect and algorithm efficiency.
【學(xué)位授予單位】：南京理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：U495;TP751

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本文編號：1756862