利用電腦自動化對數值高程模型作線形偵測｜國立中央大學博碩士論文系統

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研究生：	潘彥男 Yen-Nan Pan
論文名稱：	利用電腦自動化對數值高程模型作線形偵測 Computer Aided Algorithm for Automatic Lineament Detection in Digital Elevation Model
指導教授：	任玄 Hsuan Ren
口試委員:
學位類別：	碩士 Master
系所名稱：	地球科學學院 - 太空科學研究所 Graduate Institute of Space Science
畢業學年度：	95
語文別：	中文
論文頁數：	72
中文關鍵詞：	高斯金字塔、透空度分析、數值高程模型、線形偵測、期望最大值演算法
外文關鍵詞：	Gaussian Pyramid, EM, DEM, lineament detection, openness
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查詢本校圖書館目錄查詢臺灣博碩士論文知識加值系統勘誤回報

本論文特以數值高程模型(DEM)分析地形，利用電腦程式自動化萃取影像中的線形資訊，並進一步分析線形方向分佈，以期提供地質學者分析應用。
數值高程模型利用光達或影像對，計算了各個位置的高度值，利用此資訊可進一步計算其坡度。本研究流程首先對原始影像使用高斯金字塔降低雜訊與小線形的影響，接著利用透空度分析(Openness)，計算範圍圓內的八個天頂角以及天底角，再經由期望值最大(EM)演算法計算門檻值萃取出山脊線及山谷線。
最後在線段追蹤以及方向統計，將萃取出的山脊部份，使用細線化將每個線段化簡成一個像元寬度，使用Lee & Jyrkenvich所提出的線段追蹤演算法進行線段追蹤，再進行每個點的方向統計，以分析山脈走向。最後將影像分成許多小區塊，並分別統計方向，分析不同區塊的山脈走向。
我們使用台灣西南地區的數值高程模型作為測試資料進行實驗，並於高通濾波與人工結果比較驗證

In this paper we analyzed the topography from Digital Elevation Model (DEM) and designed a computer aided algorithm to automatically extract the lineament information in the image. In addition, we also analyzed the distribution of direction of lineament. The extracted information offers useful data to geological analysis and their applications.
DEM providing the elevation value of each coordinate is calculated from LIDAR or the image pairs. It can also be used to calculate the slope. The proposed procedure has four steps. Firstly, it uses the Gaussian Pyramid to reduce the influence of noise and short lineament from the original image. Secondly, Openness is adapted to calculate the zenith and nadir angle of eight azimuth in circular range. And then the data is thresholded to extracts the mountain ridge and valley line via EM algorithms.
Finally, in line tracing and gathering directional statistics, we use thining rule to make the extracted ridge to one pixel width, then track the line with algorithm proposed by Lee & Jyrkenvich. In direction distribution analysis we calculate the direction of each pixel on the extracted line and draw the histogram for the whole area. We also apply the same procedure to the small blocks divided from the image to have localized analysis.
We use the DEM of the southwest of Taiwan as the test data to carry on the experiment, and to verify in the high pass filtered and artificial result.

摘 要..................................................i
Abstract...............................................ii
目 錄..................................................iii
圖 目 錄...............................................v
第一章 緒論............................................1
1.1、研究動機與目的....................................1
1.2、數值高程模型介紹..................................2
1.3、研究方法與流程....................................5
1.4、論文架構..........................................6
第二章 線形特徵萃取....................................8
2.1、金字塔影像........................................8
2.1.1、高斯金字塔......................................9
2.1.2、拉普拉斯金字塔.................................13
2.2、透空度分析(Openness).............................14
2.3、期望值最大(Expectation Maximization)演算法.......17
第三章 線段處理.......................................22
3.1、線段細線化之研究.................................22
3.2線段追蹤...........................................26
3.3方向統計...........................................30
第四章 實驗成果.......................................32
4.1、實驗影像介紹.....................................32
4.2、高斯金字塔.......................................33
4.3、透空度分析.......................................36
4.4、線段處理.........................................46
4.4.1、線段追蹤.......................................47
4.4.2、線段統計.......................................49
4.5、成果比較.........................................52
4.5.1、拉普拉斯處理過程...............................52
4.5.2、人工選取山脊...................................57
第五章 結論...........................................61
參考資料..............................................63

                                

[1]Miller, C. L. and R. A. Leflamme, “The Digital Terrain Model-Theory and application,” Photo. Eng., V.24, p.433-442, 1958.
[2] Yokoyama, R., M. Shirasawa and R. Pike, “Visualizing Topography by Openness: A New Application of Image Processing to Digital Elevation Models,” PE & RS, Vol. 68, No. 3, pp. 257-265, March 2002.
[3]Lakhwinder, S., “Extraction of Different Building From Lidar Data,” ASPRS Annual Conference Reno, Nevada, May 1-5, 2006.
[4] Burt, P. J. and E. H. Adelson, “The Laplacian Pyramid as a Compact Image Code,” IEEE Trans. on Communication., vol. COM-31, no. 4, pp. 532-540, April. 1983.
[5]Gonzalez, R. C. and R. E. Wood, Digital Image Processing, Addison-Wesley Publishing, USA, 1992.
[6]Lam, L., S. W. Lee and Y. S. Ching, "Thinning Methodologies-A Comprehensive Survey," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 14, No. 9, pp.869-885, September 1992.
[7]Duda, R. O. and P. E. Hart, “Use of Hough Transformation To Detec Lines and Curves in Pictures,” Graphics and Image Processing, Commun., ACM, Vol.15, NO.1, pp.11-15.
[8] Lee, J .S. and I. Jyrkenvich, “ Coastline Detection and Tracing in SAR Images,” IEEE Tran. Geosci. Remote Sensing, Vol. 28, pp. 662-668, 1990.
[9]Todd, K. M., “The Expectation-Maximization Algorithm,” IEEE Signal Processing Magazine, pp.47-60. November 1996.
[10]洪義凱, “合成孔徑雷達影像之地形線形特徵萃取,” 國立中央大學太空科學研究所碩士論文, 94年度
[11]徐啟崇, “光學與合成孔徑雷達影像特徵分析於灘線萃取之研究.” 國立中央大學土木工程研究所碩士論文, 87年度
[12]陳彥傑, “台灣山脈的構造地形指標特性—以面積高度積分、地形碎形參數與河流坡降指標為依據,” 國立成功大學地球科學研究所博士論文, 92年度

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