發(fā)布時間：2019-05-10 18:38

【摘要】：地形特征線的提取研究作為地理信息技術(shù)中的基礎(chǔ)環(huán)節(jié)是不容忽視的,在基于樣本的地形合成等領(lǐng)域都有很好的應(yīng)用。在數(shù)字高程模型中包含了很多重要的地形特征信息,其中山脊線和山谷線是地形特征信息中最重要的特征線。能否準(zhǔn)確的從地形中提取出山脊線和山谷線的特征信息,直接影響著基于樣本的地形合成系統(tǒng)的效果。因此,本文針對地形特征線提取方法中可以改進(jìn)的方面,設(shè)計了一種新的顯著度可控的地形特征線提取算法,與現(xiàn)有的算法進(jìn)行實驗對比。同時,將本文的算法應(yīng)用于一套基于樣本的地形合成系統(tǒng)。本文的創(chuàng)新點如下:(1)提出了一種基于顯著度值的細(xì)線化算法。該算法從特征點的特征顯著程度出發(fā),使特征線雛形細(xì)化過程中挑選待剔除的特征點時,能夠保留特征更為明顯的特征點,以此達(dá)到細(xì)化后的特征線能夠保持較強特征性。同時,相比于傳統(tǒng)的細(xì)線化算法,本文算法在對特征線細(xì)化后能夠保持更好的特征線形態(tài)。(2)提出了一種環(huán)路檢測與破環(huán)算法。該算法按照掃描線的順序,利用深度優(yōu)先遍歷方法對非特征像素點進(jìn)行數(shù)值填充,使得非特征像素點以區(qū)域形式進(jìn)行劃分。通過對區(qū)域的分類,能夠?qū)崿F(xiàn)對環(huán)路區(qū)域與非環(huán)路區(qū)域的分類,而區(qū)域內(nèi)部非特征點數(shù)量的統(tǒng)計,能夠?qū)崿F(xiàn)對大型環(huán)路與小型環(huán)路的歸類。最后,根據(jù)對每一個小型環(huán)路區(qū)域邊界線段的檢測,篩選特征性最弱的邊界線段進(jìn)行剔除,從而實現(xiàn)小型環(huán)路的拆除以及對大型環(huán)路的保留。(3)提出了一種特征圖分解及特征線篩選算法。該算法以特征線分支(除端點外,組成分支的特征點度為2)為基本單元對特征圖進(jìn)行分解,從特征性最強分支開始篩選特征性最相似分支組成特征線。相比于傳統(tǒng)的方法,本文方法既避免了特征線的過度延伸,又適用于帶環(huán)路的特征圖,使得特征線呈現(xiàn)的效果更接近于實際觀察所得�；谝陨蟿�(chuàng)新點,本文設(shè)計并實現(xiàn)了一套地形特征線提取系統(tǒng),該系統(tǒng)填補了傳統(tǒng)方法中無法識別特殊地形的空白,且提取的特征線效果更加符合實際。同時,本文還實現(xiàn)了一套基于樣本的地形合成系統(tǒng),將本文提出的地形特征線提取方法應(yīng)用于系統(tǒng)中,使得合成過程中能找到更合適的特征匹配塊。
[Abstract]:As the basic link of geographic information technology, the extraction of terrain feature lines can not be ignored, and has good applications in sample-based terrain synthesis and other fields. There are many important topographic feature information in the digital elevation model, among which ridge line and valley line are the most important feature lines in terrain feature information. Whether the feature information of ridge line and valley line can be extracted accurately from terrain directly affects the effect of sample-based terrain synthesis system. Therefore, a new terrain feature line extraction algorithm with controllable saliency is designed in this paper, which can be improved in the terrain feature line extraction method, and the experimental results are compared with the existing algorithms. At the same time, the proposed algorithm is applied to a sample-based terrain synthesis system. The innovations of this paper are as follows: (1) A fine line algorithm based on saliency value is proposed. Based on the feature saliency of the feature points, the algorithm can preserve the feature points with more obvious features when the feature points to be eliminated are selected in the process of feature line refinement, so that the refined feature lines can maintain strong characteristics. At the same time, compared with the traditional fine line algorithm, this algorithm can maintain a better feature line shape after thinning the feature line. (2) A loop detection and loop breaking algorithm is proposed. According to the order of scanning lines, the depth-first traverse method is used to populate the non-feature pixels, so that the non-feature pixels are divided in the form of regions. Through the classification of the region, the classification of the loop area and the non-loop area can be realized, and the statistics of the number of non-characteristic points in the region can realize the classification of the large loop and the small loop. Finally, according to the detection of the boundary line segment of each small loop area, the boundary segment with the weakest characteristic is screened out. Thus, the removal of small loop and the retention of large loop are realized. (3) A feature graph decomposition and feature line screening algorithm is proposed. In this algorithm, the feature line branch (except the end point, the characteristic point degree of the component branch is 2) is used as the basic unit to decompose the feature graph, and the characteristic line is selected from the strongest characteristic branch to form the characteristic line. Compared with the traditional method, this method not only avoids the overextension of the feature line, but also is suitable for the feature map with loop, so that the effect of the feature line presentation is closer to the actual observation. Based on the above innovations, a set of terrain feature line extraction system is designed and implemented in this paper, which fills in the blank that the traditional method can not recognize the special terrain, and the effect of the extracted feature line is more in line with the reality. At the same time, this paper also implements a set of sample-based terrain synthesis system, and applies the terrain feature line extraction method proposed in this paper to the system, so that more suitable feature matching blocks can be found in the synthesis process.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：P208

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