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  本文選題：高分辨率遙感　切入點：道路提取　出處：《中國礦業(yè)大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：高分辨率遙感是近年來遙感領(lǐng)域發(fā)展極為迅速的一項技術(shù)，它為對地觀測領(lǐng)域提供了豐富、海量的空間數(shù)據(jù)。道路是高分辨率遙感影像中一項十分重要的特征。從高分辨率遙感影像中提取道路，是高分辨率遙感影像分析、解譯和應(yīng)用的一個前沿課題，，有著重要的理論和現(xiàn)實意義，在現(xiàn)實生活中有非常廣泛的應(yīng)用。雖然已經(jīng)有大量有關(guān)道路提取的算法，但是由于自然場景的復(fù)雜性、遙感影像的噪聲和算法的局限性，道路提取并沒有得到完美地解決，其依然是一個研究的熱點和難點。 本文從多特征角度出發(fā)，研究影響道路提取精度的因素，提出了基于多特征的高分辨率遙感影像道路提取算法，提高了道路提取的精度。研究內(nèi)容包括道路形狀特征、光滑道路中心線提取以及面向?qū)ο蟮牡缆诽崛�。研究成果為高分辨率遙感影像道路提取提供了一套新的解決方案。本文具體的研究工作主要有： （1）構(gòu)建了一種道路形狀特征指標。本文提出的形狀指標可以更加有效地描述道路的幾何特征，濾除非線性特征，提高了道路提取精度。 （2）提出了一種光滑的道路中心線提取算法。該算法使用張量投票將道路網(wǎng)絡(luò)分解為獨立的道路段，然后利用回歸算法從道路段中提取道路中心線。試驗結(jié)果表明，本文提出的中心線提取算法不會產(chǎn)生類似傳統(tǒng)細化算法的毛刺現(xiàn)象，結(jié)果比較光滑。 （3）提出了一種基于多特征的道路提取算法。該方法融合了形狀特征、圖像分割和圖像分類，試驗結(jié)果表明該算法具有較高的精度和穩(wěn)定性。
[Abstract]:High-resolution remote sensing is one of the most rapidly developing technologies in the field of remote sensing in recent years, which has provided a wealth for the field of Earth observation, Massive spatial data. Road is a very important feature in high-resolution remote sensing image. Extracting road from high-resolution remote sensing image is a forward topic in the analysis, interpretation and application of high-resolution remote sensing image. Has important theoretical and practical significance, has very extensive application in the real life. Although there have been a large number of road extraction algorithms, but due to the complexity of natural scenes, remote sensing image noise and the limitations of the algorithm, Road extraction has not been solved perfectly, and it is still a hot and difficult point. From the point of view of multi-feature, this paper studies the factors that affect the road extraction accuracy, and proposes a high-resolution remote sensing image road extraction algorithm based on multi-feature, which improves the accuracy of road extraction. Smooth road centerline extraction and object-oriented road extraction. The research results provide a new solution for high-resolution remote sensing image road extraction. 1) A road shape feature index is constructed, which can more effectively describe the geometric features of the road, filter out the nonlinear features, and improve the road extraction accuracy. (2) A smooth road centerline extraction algorithm is proposed, in which Zhang Liang is used to decompose the road network into independent road segments, and then the regression algorithm is used to extract the road centerline from the road segment. The experimental results show that, The centerline extraction algorithm presented in this paper does not produce burr phenomenon similar to the traditional thinning algorithm, and the result is smooth. (3) A multi-feature based road extraction algorithm is proposed, which combines shape features, image segmentation and image classification. The experimental results show that the algorithm has high accuracy and stability.
【學(xué)位授予單位】：中國礦業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：P237

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