發(fā)布時(shí)間：2018-04-06 05:09

  本文選題：多視影像匹配　切入點(diǎn)：半全局約束立體影像匹配　出處：《中南大學(xué)》2013年碩士論文

【摘要】：覆蓋同一區(qū)域的大重疊度影像為影像匹配提供大量的冗余信息,因此多視影像匹配成為數(shù)字?jǐn)z影測(cè)量的研究熱點(diǎn)。多視影像具有重疊度高的特點(diǎn),因此,如何在匹配過(guò)程中充分利用多視影像的冗余信息,是多視影像匹配的關(guān)鍵。針對(duì)影像匹配可靠性問(wèn)題,本文提出兩種基于半全局優(yōu)化的多視影像匹配方法,在獲取密集匹配點(diǎn)云的基礎(chǔ)上,對(duì)三維重建進(jìn)行了研究。本文主要研究?jī)?nèi)容如下： (1)針對(duì)斷裂遮擋、紋理單一及紋理缺乏等匹配困難區(qū)域,本文提出一種基于像方串點(diǎn)的半全局多視影像匹配方法。通過(guò)對(duì)所有已校正的立體像對(duì)進(jìn)行半全局約束立體影像匹配,根據(jù)所有立體像對(duì)得到的同名點(diǎn)通過(guò)傳遞追蹤的方法實(shí)現(xiàn)多視影像串點(diǎn),然后利用多片前方交會(huì)迭代優(yōu)化實(shí)現(xiàn)匹配結(jié)果在物方的融合,形成一個(gè)整體的匹配結(jié)果。多視影像匹配具有較大的匹配冗余,可以提高匹配的可靠性,同時(shí)多片前方交會(huì)迭代優(yōu)化有利于提高交會(huì)精度,為后續(xù)三維建模提供密集可靠的點(diǎn)云。 (2)針對(duì)單立體匹配模式在遮擋區(qū)域容易產(chǎn)生歧義性匹配,且在紋理單一及紋理缺乏區(qū)域容易產(chǎn)生“多義性”匹配問(wèn)題,本文提出一種基于物方幾何約束的半全局多視影像匹配方法。根據(jù)影像的成像關(guān)系,在物方幾何約束下引導(dǎo)多視影像同時(shí)進(jìn)行匹配,通過(guò)半全局優(yōu)化方法減少錯(cuò)誤匹配。采用由粗到精的金字塔影像匹配策略,利用低分辨率影像匹配結(jié)果約束高分辨率影像匹配,實(shí)現(xiàn)匹配傳播,減少由于匹配模糊導(dǎo)致的錯(cuò)誤匹配,同時(shí)有利于減少內(nèi)存消耗以及降低計(jì)算復(fù)雜度。 (3)在獲取密集可靠的點(diǎn)云基礎(chǔ)上,利用Possion表面重建重構(gòu)場(chǎng)景幾何拓?fù)浣Y(jié)構(gòu),并將對(duì)應(yīng)影像的紋理映射到三維模型上,獲取具有真實(shí)感的場(chǎng)景模型。 本文提出兩種基于半全局優(yōu)化的多視影像匹配方法,其理論、算法和有關(guān)試驗(yàn)使用Visual Studio2010實(shí)現(xiàn)。有關(guān)試驗(yàn)結(jié)果證明本文方法能為三維建模提供密集可靠的三維點(diǎn),為高精度三維重建提供一條可靠的途徑。
[Abstract]:Large overlap images covering the same area provide a lot of redundant information for image matching, so multi-view image matching has become a hot topic in digital photogrammetry.Multi-view image has the characteristics of high overlap. Therefore, how to make full use of redundant information in multi-view image matching is the key to multi-view image matching.Aiming at the reliability of image matching, this paper presents two methods of multi-view image matching based on semi-global optimization. Based on the acquisition of dense matching point clouds, 3D reconstruction is studied.The main contents of this paper are as follows:In this paper, a semi-global multi-view image matching method based on image square string points is proposed for difficult areas such as fault occlusion, single texture and lack of texture.By matching all corrected stereo pairs with semi-global constraint stereo image, according to the same name points obtained from all stereo pairs, multi-view image string points are realized by transfer tracing method.Then the multi-slice forward intersection is used to optimize the fusion of the matching results in the object side to form a whole matching result.Multi-view image matching has a large matching redundancy, which can improve the reliability of matching. At the same time, the iterative optimization of multi-slice forward rendezvous is beneficial to improve the rendezvous accuracy and provide a dense and reliable point cloud for the subsequent 3D modeling.(2) in view of the ambiguity matching in the occlusion region of the single stereo matching pattern, and the "polysemy" matching problem in the single texture and the lack of texture region,In this paper, a semi-global multi-view image matching method based on object-square geometric constraints is proposed.According to the imaging relation of the image, the multi-view image can be matched simultaneously under the constraint of object geometry, and the error matching can be reduced by semi-global optimization method.By using the coarse to fine pyramid image matching strategy, the low resolution image matching result is used to constrain the high resolution image matching, and the matching propagation is realized, and the error matching caused by the matching fuzzy is reduced.At the same time, it can reduce memory consumption and computational complexity.On the basis of obtaining dense and reliable point cloud, the scene geometry topology is reconstructed by Possion surface reconstruction, and the texture of the corresponding image is mapped to the 3D model to obtain the realistic scene model.In this paper, two methods of multi-view image matching based on semi-global optimization are proposed. The theory, algorithm and related experiments are implemented with Visual Studio2010.The experimental results show that this method can provide dense and reliable 3D points for 3D modeling and provide a reliable way for high precision 3D reconstruction.
【學(xué)位授予單位】：中南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP391.41;P231.5

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本文編號(hào)：1718093