(3.233.221.149) 您好!臺灣時間:2020/02/23 06:47
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
本論文永久網址: 
line
研究生:許君韶
研究生(外文):Chun-Shao Hsu
論文名稱:區塊分割變遷偵測法於多時期衛星影像之應用
論文名稱(外文):Segmentation-based change detection method for remotely sensed images
指導教授:陳繼藩
指導教授(外文):Chi-Farn Chen
學位類別:碩士
校院名稱:國立中央大學
系所名稱:土木工程研究所
學門:工程學門
學類:土木工程學類
論文出版年:2005
畢業學年度:93
語文別:中文
論文頁數:99
中文關鍵詞:區塊化分割統計測試變遷偵測資料挖掘
外文關鍵詞:Data mining techniqueChange detectionSegmentationStatistical test
相關次數:
  • 被引用被引用:8
  • 點閱點閱:227
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:35
  • 收藏至我的研究室書目清單書目收藏:0
土地覆蓋和土地利用的變遷偵測是遙測影像上一項重要的應用。影像變遷偵測有兩個重要的工作:(1)變遷區域之偵測(2)類別變化之偵測。過去在傳統上主要是以像元為基礎的方式來進行變遷區域偵測的工作,在偵測的結果上往往會出現許多如像元大小般的雜訊。因此,在本研究中提出以區塊為基礎的技巧,來進行變遷偵測的工作。本研究主要的方式是對多時期影像先進行合併的工作,再利用區塊增長法(region growing)對於合併後的影像進行區塊化的分割,接著再應用統計上的顯著水準測試來檢驗區塊有無變遷情形發生。最後,利用資料挖掘(data mining)之技術建立類別知識庫,來尋變遷區塊之類別變化情形。此方法實際運用在模擬影像及SPOT5影像上進行實驗的測試與評估,其結果顯示本研究所提出以區塊為基礎及資料挖掘技術的變遷偵測方式,可提供完整的變遷區塊及類別變遷的資料。
Land cover/land use change detection has been an important application of remotely sensed images. Basically, a practical change detection algorithm is expected to provide a complete information about the change that includes changed locations and categories. Unlike the pixel-based change detection methods, which normally generate pixel-sized noises, this study develops a segmentation-based change detection technique. The main idea of the study is to apply region growing segmentation to multi-dated composite images, and divide the images into many regions. Then a statistical significance test is used to find out the regions that have been changed or not. Thereafter, a knowledge-based system developed by the data mining technique is used to find out the category change for each changed region. An experiment is performed to detect the changed areas with simulated and SPOT5 images, and the result shows that the segmentation-based change detection method combined with data mining technique can provide region-liked changed map as well as the change information about the category.
摘要 I
ABSTRACT II
目錄 IV
圖目錄 VII
表目錄 XI
第一章 序論 1
1-1 前言 1
1-2 文獻回顧 2
1-2-1 變遷偵測法 3
1-2-2 影像區塊分割 9
1-2-3 偵側類別變化 13
1-3 研究目的與方法概述 14
1-4 章節簡介 17
第二章 區塊變遷偵測 19
2-1資料前處理 21
2-1-1 幾何校正 21
2-1-2 輻射校正 21
2-1-3合併多時期影像 22
2-2區塊分割 22
2-2-1區塊增長法 23
2-2-2 區塊增長法之參數意義 28
2-3統計檢定進行區塊變遷偵測 30
2-3-1卡方檢定之理論基礎 31
2-3-2 卡方檢定應用於區塊的變遷偵測 32
第三章 偵測類別變化 35
3-1類別變化簡介 36
3-2資料挖掘概念 37
3-3資料挖掘應用 39
3-3-1輸入訓練資料 40
3-3-2建立類別知識庫 41
3-3-2-1決策樹 42
3-3-2-2分類及回歸決策樹演算法(CART) 43
3-3應用資料挖掘技術偵測類別變化 45
第四章 測試與成果分析 47
4-1模擬影像 47
4-1-1 模擬影像製作 47
4-2 SPOT5影像 59
4-2-1 SPOT 影像簡介 59
4-2-2第ㄧ組SPOT5影像 61
4-2-3第二組SPOT5影像 71
4-3精度分析 83
4-3-1 檢核變遷偵測之正確性 84
4-3-2 檢核類別變化情形之正確性 88
第五章 結論與建議 94
5-1 結論 94
5-2建議 96
參考文獻 97
黃俊英 (1985) "多變量分析", 中國經濟企業研究所,華泰文化事業公司
王文俊 編著, 認識Fuzzy, 全華科技圖書, 1986
徐維政 (2003) ”改良式變異向量分析法於變遷偵測之探討” ,碩士論文, 國立中央大學土木工程研究所
張紘炬 (2002) ”統計學”,華泰書局

Berry, M. and G. Linoff, (1997) “Data Mining Techniques for Marketing, Sales, and Customer Support,” John Wiley & Sons

Byrne, G., P. Crapper, and K. Mayo, (1980)“Monitoring Land-cover Change by Principal Component Analysis of Multitemporal Landsat Data”, Remote Sensing Environ., Vol.10, pp.175-184

DEFINIENS, eCognition object oriented image analysis, User Guide 3
http://www.definiens-imaging.com/index.htm

Haralick, R., and L. Shapiro, (1985) “Survey : Image Segmentation Techniques”, Computer Vision, Graphics, and Image Processing, vol. 29,
pp. 100-132.

Hastie, T. ; R.Tibshirani, ; J. Friedman, (2001) "The Elements of Statistical Learning: Data Mining, Inference, and Prediction", Spring Series in Statistics.

Jensen, J. R., K. Rutchey, M. S. Koch, S. Narumalani , (1995),”Inland Wetland Change Detection in the Everglades Water Conservation Area Using a Time Series of Normalized Remotely Sensed Data”, Photogrammetric Enginneering & Remote Sensing ,Vol. 61,No. 2,pp.199~209.

Kruse, F., A. Lefkoff, J. Boardman, K. Heidebrecht, A. Shapiro, P. Barloon and A. H. Geotz, (1993) “The Spectral Image Processing System (SIPS) – Interactive Visualization and Analysis of Imageing Spectromator Data”, Remote Senseing of the Environment, vol.44, pp 145-163.

Lillesand, T., and R. Keifer, (2004) “Remote Sensing and Image Interpretation”, Second Edition, John Wiley & Sons

Maselli, F., A. Rodolfi , C. Conese , (1996)” Fuzzy Classification of Spatially Degraded Thematic Mapper Data for the Estimation of Sub-Pixel Components”, International Journal of Remote Sensing,Vol. 17,No. 3,pp.537~551.

Pekkarinen, A.,( 2002) “A Method For the Segmentation of Very High Resolution Images of Forested Landscapes”, International Journal of Remote Sensing, vol. 23, no. 14, pp. 2817-2836.

Richards, J., (1984)“Thematic Mapping from Multitemporal Image Data Using the Principal Components Transformation”, Remote Sensing Environ., Vol.16

Richards, J., and X. Jia, (1999) “Remote Sensing Digital Image Analysis : an Introduction”, Speinger-Verlag Berlin Heidelberg New York.

Rubec, C., and J. Thie., (1987) “Land Use Monitoring with Landsat Digital Data in Southwestern Manitoba”, Proceedings of the fifth Canadian Symposium on Remote Sensing, Victoria, BC, pp. 136-150
Sappa, A., and M. Devy, (2001) “Fast Range Image Segmentation by an Edge Detection Strategy”, IEEE 3rd International Conference on 3-D
Digital Imaging and Modeling, Quebec City, Canada.

Shafarenko, L., M. Petrou, , and J. Kittler,( 1997) “Automatic Watershed
Segmentation of Randomly Textured Color Images”, IEEE Trans. Image
Processing, vol. 6, no. 11, pp. 1530-1543.

Singh, A., ( 1986) “Change Detection in the Tropical Forest Environmental of Northern India Using Landsat”, Remote Sensing and Tropical Land Management,M.J. Eden and J.T. Parry, Eds. John Wiley & Sons, London, pp.237-254

Stauffer, M. and R. McKinney, (1978)“Landsat Image Differencing as an Automated Land Cover Change Detection Technique”, Computer Sciences Corporation, Technical Memorandum CSC/TM-78/6215 Silver Spring, MD

Stow, D. , L. Tinney, and J. Estes, (1980) “Deriving Land Use/Land Cover Change Statistics form Landsat: A Study of Prime Agricultural Land”,Proceeding of the 14th International Symposium on Remote Sensing of Environment, pp. 1227-1237

Weismiller, R., S. Kristoof, D. Scholz, P. Anuta, and S.A. Momen, (1977) “Change Detection in Coastal Zone Environments”, Photogrammetric Engineering and Remote Sensing”, Vol.43, pp.1533-1539

Yamamoto, T., and H. Hiroshi, (2001) “A Change Detection Method for Remotely Sensed Multispectral and Multitemporal Image Using 3-D Segmentation”, IEEE Trans. Geosci. Remote Sensing, Vol.39 , No.5, May
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊
 
系統版面圖檔 系統版面圖檔