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基于機(jī)載LIDAR點(diǎn)云數(shù)據(jù)的建筑物邊緣提取

發(fā)布時(shí)間:2018-03-05 19:20

  本文選題:LIDAR數(shù)據(jù) 切入點(diǎn):DSM深度影像 出處:《長安大學(xué)》2013年碩士論文 論文類型:學(xué)位論文


【摘要】:上世紀(jì)末,機(jī)載LIDAR技術(shù)在三維地球空間信息的實(shí)時(shí)獲取方面有了突飛猛進(jìn)的發(fā)展,成為一種獲取高時(shí)空分辨率地球空間信息的全新技術(shù)手段。由于能夠自動(dòng)的、快速精確的、不受天氣影響的獲取三維坐標(biāo),使人們從傳統(tǒng)的人工單點(diǎn)地形表面數(shù)據(jù)獲取變成連續(xù)自動(dòng)的數(shù)據(jù)獲取,為地形地物識(shí)別提供了新的數(shù)據(jù)源和信息源。因此,如何從LIDAR數(shù)據(jù)中自動(dòng)化、智能化識(shí)別地物成為需要解決的關(guān)鍵問題和新的研究領(lǐng)域。 本文以機(jī)載LIDAR點(diǎn)云數(shù)據(jù)為基礎(chǔ),通過一定的算法進(jìn)行數(shù)據(jù)空洞填補(bǔ),將離散LIDAR點(diǎn)云數(shù)據(jù)進(jìn)行規(guī)則格網(wǎng)重采樣,得到數(shù)字表面模型(DSM),接著按照高程進(jìn)行灰度量化生成DSM深度影像,通過直方圖閾值分割、小面積去除等操作對DSM深度影像進(jìn)行預(yù)處理,得到獨(dú)立的建筑物區(qū)域。最后運(yùn)用Canny邊緣檢測算子檢測建筑物的粗略邊緣,利用hough變換獲得建筑物邊緣的直線段組,通過線段合并將本應(yīng)該屬于一條直線段的破碎小線段合并,通過直角約束對線段的傾角進(jìn)行調(diào)整,獲得了符合實(shí)際情況的建筑物邊緣信息。 本文以機(jī)載LIDAR點(diǎn)云為基礎(chǔ),在無其他輔助數(shù)據(jù)的情況下,運(yùn)用ArcGIS、ERDAS等軟件進(jìn)行數(shù)字圖像處理,運(yùn)用MATLAB軟件進(jìn)行算法優(yōu)化,實(shí)現(xiàn)了基于航空LIDAR點(diǎn)云數(shù)據(jù)的建筑物邊緣檢測。
[Abstract]:At the end of 0th century, airborne LIDAR technology has made rapid progress in the real-time acquisition of three-dimensional geospatial information, and has become a new technology for obtaining geospatial information with high spatial and temporal resolution. The acquisition of 3D coordinates, which is not affected by weather, makes people change from traditional artificial single-point topographic surface data acquisition to continuous automatic data acquisition, which provides a new data source and information source for terrain and ground object recognition. How to automate and intelligently identify ground objects from LIDAR data has become a key problem and a new research field. In this paper, based on airborne LIDAR point cloud data, a certain algorithm is used to fill the data holes, and discrete LIDAR point cloud data are resampled by regular grid resampling. The digital surface model (DSM) is obtained, and then the DSM depth image is generated according to the grayscale of height. The DSM depth image is preprocessed by histogram threshold segmentation, small area removal and so on. Finally, Canny edge detection operator is used to detect the rough edge of the building, hough transform is used to obtain the straight line segment group of the building edge, and the broken small line segment which is supposed to belong to a straight line segment is merged through line segment merging. The obliquity of the line segment is adjusted by the right angle constraint, and the building edge information is obtained according with the actual situation. Based on airborne LIDAR point cloud and without other auxiliary data, this paper uses ArcGIS ERDAS and other software to process digital image, and uses MATLAB software to optimize the algorithm to realize building edge detection based on airborne LIDAR point cloud data.
【學(xué)位授予單位】:長安大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2013
【分類號(hào)】:P23

【引證文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前1條

1 樊敬敬;基于機(jī)載LiDAR點(diǎn)云數(shù)據(jù)的城區(qū)植被與建筑物提取研究[D];中國礦業(yè)大學(xué);2016年



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