【摘要】：傾斜攝影能夠全方位、高效地獲取建筑物立面信息,在城市三維重建中表現(xiàn)出獨(dú)特的優(yōu)勢(shì),已成為一種重要的數(shù)據(jù)獲取方式。影像密集匹配技術(shù)是對(duì)立體像對(duì)逐像素地建立對(duì)應(yīng)關(guān)系,根據(jù)三角測(cè)量原理獲得像素的三維空間位置。傾斜攝影相對(duì)于傳統(tǒng)的垂直攝影方式,不同相機(jī)的拍攝視角差異較大,影像包含地物種類錯(cuò)綜復(fù)雜,不同地物深度變化范圍較廣,地物之間有明顯的遮擋,這給傾斜影像密集匹配帶來挑戰(zhàn)。針對(duì)航空傾斜影像深度變化范圍大、紋理缺乏導(dǎo)致的自適應(yīng)匹配難題,本文比較現(xiàn)有的立體像對(duì)匹配方法,以高效的半全局立體匹配算法為基礎(chǔ),在匹配過程中引入紋理信息約束,自適應(yīng)調(diào)整匹配參數(shù),提高算法對(duì)不同地形、不同地物的匹配能力。本文的主要研究內(nèi)容如下:(1)通過分析比較不同的影像紋理檢測(cè)的算法,采用較為魯棒的方法來定量描述影像的紋理特征,該紋理特征能夠在一定程度上反映像素的深度變化,在匹配的過程中顧及到紋理信息,能夠顯著提高匹配結(jié)果精度。(2)為了降低匹配算法對(duì)參數(shù)的敏感,本文以像素的紋理屬性為依據(jù),對(duì)不同紋理屬性的像素,采用不同的匹配代價(jià)組合策略,同時(shí)為了增強(qiáng)初始匹配代價(jià)的魯棒性,對(duì)弱紋理的區(qū)域進(jìn)行代價(jià)聚合。在匹配階段,自適應(yīng)地計(jì)算像素的半全局匹配的懲罰參數(shù),在不同紋理區(qū)域采用不同的平滑性約束,克服點(diǎn)云噪聲、無法保留視差斷裂帶的問題。(3)研究采用GPGPU實(shí)現(xiàn)上述匹配過程,提高對(duì)無人機(jī)傾斜影像的處理效率,使得該算法能夠應(yīng)用在實(shí)際的三維生產(chǎn)中。
[Abstract]:The oblique photography can obtain the facade information in all directions and efficiently. It has shown unique advantages in the three dimensional reconstruction of the city. It has become an important method of data acquisition. The image intensive matching technique is a pixel by pixel based on the establishment of the corresponding relationship. Compared with the traditional vertical photography, the different cameras have a large difference in shooting angle, the image contains the complex types of objects, the range of the depth of different objects is wide and there is a clear occlusion between the objects. This brings a challenge to the intensive matching of the inclined images. In order to match the matching problem, this paper compares the existing stereo pair matching method, based on the efficient semi global stereo matching algorithm, and introduces the texture information constraint in the matching process, adaptively adjusts the matching parameters, and improves the matching ability of the algorithm to different terrain and different objects. The main contents of this paper are as follows: (1) through analysis and comparison, the main contents of this paper are as follows: The same image texture detection algorithm uses a more robust method to quantitatively describe the texture features of the image. The texture features can reflect the depth of the pixel to a certain extent, and the texture information is taken into account in the matching process. (2) in order to reduce the sensitivity of the matching algorithm to the parameters, this paper is to reduce the sensitivity of the matching algorithm to the parameters. Based on the texture properties of pixels, the pixels with different texture attributes are combined with different matching costs. At the same time, in order to enhance the robustness of the initial matching cost, the region of the weak texture is aggregated. In the matching phase, the penalty parameters for the half full match of the pixels are calculated adaptively, and the different texture regions are not used. The same smoothing constraint can overcome the point cloud noise and can not retain the problem of parallax fault zone. (3) the study of using GPGPU to achieve the above matching process is used to improve the processing efficiency of the unmanned aerial vehicle (UAV) image, so that the algorithm can be applied to the actual three-dimensional production.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41

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