臺灣博碩士論文加值系統

摘 要
由於IKONOS衛星影像具有甚高之空間解析度，對於大比例尺製圖而言具有相當高的潛力。因此本研究之重點即為考慮地形起伏、建築物存在及相互遮蔽問題之IKONOS衛星影像正射化為主要工作。
就IKONOS衛星而言，無法取得原始影像，因此以其使用率最高的GEO等級影像為本研究之標的。因考慮地形及房屋在影像中所造成的遮蔽，故所產生之正射影像稱為“真實正射影像”。
研究之方法包括：(1)對地面控制點進行高差移位改正，(2)進行影像坐標與地面坐標間之二維轉換，(3)對正射影像之每一個像元進行反投影，(4)使用數值地形模型進行前步驟所得像元之高差移位校正，(5)影像重新取樣。針對真實正射影像之產生尚需進行房屋區高差移位校正及遮蔽區處理。實驗成果顯示，在僅使用6個地面控制點之情況下，不論是僅考慮數值地形模型所產生之正射影像或使用房屋模型所產生之真實正射影像，其定位誤差均優於2m。
關鍵詞：IKONOS，正射影像，高差移位，仿射轉換

ABSTRACT
Due to its high spatial resolution, IKONOS imagery has a very high potential for large-scale topographic mapping. The focus of this investigation is performing the geometric correction for the IKONOS satellite images.
Since raw image data would, in general, not be provided by the satellite company, we have developed a method that performs the rectification of IKONOS GEO images. We also considered the occlusions caused by terrain and buildings, thus, the generated orthoimages will be called the True “Orthoimage”.
The proposed scheme includes the following steps: (1) the correction of relief displacement for GCPs, (2) the performing of two dimensional transformation between the ground coordinate system and the image coordinate system, (3) the performing of back projection for each pixel in the orthoimage, (4) the use of DTM to calculate the relief displacement for the pixel in the previous step, and (5) image resampling. Relief corrections for buildings and occlusion process will also be handled toward generation of true orthoimage. The experimental results indicate that the generated orthoimages, including the ones by using DTM and the one considering building effects, may reach an accuracy of 2 m, when 6 GCPs were employed.
Keywords: IKONOS, Orthophotos, Relief Displacement, Affine Transformation

目 錄
目 錄I
圖 目 錄IV
表 目 錄VII
摘 要VIII
ABSTRACTIX
第一章 緒 論1
1.1 研究動機與目的1
1.2 研究方法與步驟2
第二章 IKONOS衛星簡介7
2.1 成像原理7
2.2 衛星成像性質8
2.2.1 軌道幾何特性8
2.2.2 空間解析度10
2.2.3 時間解析度10
2.2.4 輻射解析度11
第三章 有理函數法數學模式13
第四章 IKONOS衛星影像幾何校正17
4.1 模式誤差分析17
4.1.1 傾斜移位為線性17
4.1.2 姿態誤差對高差移位之影響20
4.2 以控制點求取系統轉換參數21
4.2.1 使用之資料22
4.2.2 高差移位的改正22
4.2.3 仿射轉換24
4.3 影像正射化26
4.3.1 使用之資料27
4.3.2 預估處理資料範圍28
4.3.3 影像反投影與正射糾正29
4.3.4 影像重新取樣30
4.4 真實正射影像30
4.4.1 使用之資料31
4.4.2 預估處理資料範圍31
4.4.3 遮蔽區域偵測32
4.4.4 高差移位之計算33
4.4.5 遮蔽區域處理35
第五章 實例測試及成果分析37
5.1 資料背景38
5.1.1 測區一 台中38
5.1.2 測區二 高雄40
5.1.3 測區三 土城、樹林及板橋影像3A及影像3B41
5.1.4 測區四 三峽及鶯歌43
5.2 有理函數法45
5.2.1 測試一 台中45
5.2.2 測試二 土城、樹林及板橋影像3A及影像3B46
5.2.2.1 土城、樹林及板橋影像3A46
5.2.2.2 土城、樹林及板橋影像3B47
5.3 影像正射化49
5.3.1 測試一 台中49
5.3.1.1 模式一 將仰角視為常數49
5.3.1.2 模式二 不同入射角(考慮FOV)50
5.3.2 測試二 高雄53
5.3.3 測試三 土城、樹林及板橋影像3A及影像3B55
5.3.3.1 土城、樹林及板橋影像3A55
5.3.3.1.1 模式一 將仰角視為常數55
5.3.3.1.2 模式二 不同入射角(考慮FOV)57
5.3.3.2 土城、樹林及板橋影像3B59
5.3.3.2.1 模式一 將仰角視為常數59
5.3.3.2.2 模式二 不同入射角(考慮FOV)60
5.3.4 測試四 三峽及鶯歌63
5.4 真實正射影像66
5.4.1 測試一 測區A68
5.4.2 測試二 測區B71
5.4.3 測試三 測區C75
5.4.4 測試四 測區D78
5.5 實驗結果總結82
5.5.1 精度評估82
5.5.2 運算效率85
第六章 結論與展望86
參考文獻88

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