本文選題：滑坡　切入點：區(qū)域生長　出處：《西南交通大學(xué)》2013年碩士論文

【摘要】：滑坡是一種很嚴重的地質(zhì)災(zāi)害現(xiàn)象,而地震是滑坡產(chǎn)生的直接誘因之一�；碌漠a(chǎn)生通常會引起人員傷亡和經(jīng)濟損失,較大的地震引起的滑坡常常會使得房屋掩埋,道路損壞以及堰塞湖的形成,特別是道路的損壞直接會使得救援通道的阻塞,影響救援速度�？焖偬崛』逻吔�,估算滑坡致災(zāi)面積,推測出滑坡的規(guī)模,對抗震救災(zāi)的快速應(yīng)急響應(yīng)提供了有效的數(shù)據(jù)支持。 從遙感影像中提取滑坡特征目前已經(jīng)有很多研究,但是仍然存在很多問題,這是由于滑坡影像特征的復(fù)雜性和多樣性。本文圍繞著滑坡邊界的快速提取開展研究,通過對近幾年來滑坡信息提取方法的分析和研究,探討了滑坡邊界提取的基本思想,對現(xiàn)有的圖像分割方法加以改進。針對不同的影像特征,本文采用了三種方法對滑坡邊界進行提取。 首先對地震產(chǎn)生的新滑坡影像特征進行探討,針對滑坡影像的特定性質(zhì)采用了基于區(qū)域生長、基于邊緣區(qū)域生長和基于K-均值聚類法這三種方法對滑坡進行邊緣提取�；趨^(qū)域生長的方法中,根據(jù)滑坡影像的色彩特征,引入顏色相似性度量作為生長的準則,將顏色相近的滑坡區(qū)域合并,再根據(jù)邊緣提取方法提取滑坡邊緣,對邊緣進行平滑、細化獲得邊界,最后對閉合的滑坡邊界進行填充估算出滑坡致災(zāi)面積。基于邊緣區(qū)域生長的方法是先對全局圖像進行邊緣提取,通過區(qū)域生長來提取滑坡區(qū)域,最后得到滑坡的邊界和致災(zāi)面積。基于K-均值聚類法是利用K-均值聚類法對圖像進行分割,對分割出來的圖像進行邊緣提取,通過區(qū)域生長方法獲得滑坡邊緣,最后量算滑坡致災(zāi)面積。本文針對提出的算法編寫了相應(yīng)的程序,包括圖像平滑、圖像分割、邊緣處理、圖像填充等功能,較好的實現(xiàn)了滑坡邊界提取和滑坡致災(zāi)面積估算功能。
[Abstract]:Landslide is a very serious geological disaster phenomenon, and earthquake is one of the direct inducements of landslide. Landslide usually causes casualties and economic losses, and landslides caused by larger earthquakes often make houses buried. The road damage and the formation of the barrier lake, especially the damage of the road, will directly block the rescue passage and affect the rescue speed. Quickly extract the landslide boundary, estimate the landslide disaster area, and speculate the scale of the landslide. It provides effective data support for rapid emergency response to earthquake relief. There have been many researches on landslide feature extraction from remote sensing images, but there are still many problems, which is due to the complexity and diversity of landslide image features. Based on the analysis and study of landslide information extraction methods in recent years, the basic idea of landslide boundary extraction is discussed, and the existing image segmentation methods are improved. In this paper, three methods are used to extract the landslide boundary. Firstly, the characteristics of the new landslide image produced by earthquake are discussed, and the region based growth is adopted in view of the specific properties of the landslide image. The edge of landslide is extracted based on the three methods of edge region growth and K-means clustering. In the method of region growth, according to the color characteristics of landslide image, the color similarity measure is introduced as the growth criterion. Combining the similar color landslide area, then extracting the landslide edge according to the edge extraction method, smoothing the edge, thinning the obtained boundary, Finally, the landslide disaster area is estimated by filling the closed landslide boundary. The method based on the growth of the edge region is to extract the edge of the global image first, and then extract the landslide area by the region growth. Finally, the boundary and disaster area of landslide are obtained. Based on K-means clustering method, the image is segmented by K-means clustering, the edge of the image is extracted, and the landslide edge is obtained by region growth method. Finally, the area caused by landslide disaster is calculated. In this paper, the corresponding program is written for the proposed algorithm, including image smoothing, image segmentation, edge processing, image filling and so on. The function of landslide boundary extraction and landslide disaster area estimation is well realized.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：P642.22;P237

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