博碩士論文 92322089 詳細資訊




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姓名 許君韶(Chun-Shao Hsu)  查詢紙本館藏   畢業系所 土木工程學系
論文名稱 區塊分割變遷偵測法於多時期衛星影像之應用
(Segmentation-based change detection method for remotely sensed images)
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摘要(中) 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。
摘要(英) 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.
關鍵字(中) ★ 區塊化分割
★ 統計測試
★ 變遷偵測
★ 資料挖掘
關鍵字(英) ★ Data mining technique
★ Change detection
★ Segmentation
★ Statistical test
論文目次 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
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指導教授 陳繼藩(Chi-Farn Chen) 審核日期 2005-7-19
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