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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 張恆華(Herng-Hua Chang) | |
dc.contributor.author | Wan-Chen Chan | en |
dc.contributor.author | 詹宛真 | zh_TW |
dc.date.accessioned | 2021-06-17T08:07:04Z | - |
dc.date.available | 2019-08-20 | |
dc.date.copyright | 2019-08-20 | |
dc.date.issued | 2019 | |
dc.date.submitted | 2019-08-19 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/73630 | - |
dc.description.abstract | 影像套合是將兩個不同來源的相同物件,透過影像轉換的方法對齊,而衛星影像擁有不同的影像型態和複雜的影像場景,以便於各種量測觀察,故衛星影像的自動影像套合方法仍然是一個具有挑戰性的研究。本論文提出一個快速與準確的方法來實現自動衛星影像套合,提出的方法分成三大步驟:第一步驟是使用已改良的尺度不變特徵轉換方法,其使用雙線性內插法的重採樣以解決原始重採樣因旋轉而特徵點位移的問題;然後將特徵描述值正規化使兩組特徵點配對更精確與健全。第二步驟是進行特徵點配對的正確與錯誤判斷,其使用隨機抽樣組合演算法對樣本特徵點進行篩檢。一方面,在達到基本抽樣次數後,當檢覈成功次數大於當前抽樣次數的一半,則歸類為正確配對,提早抽離以加快速度;另一方面,若是挑選出的正確配對數目不足,則會以目前正確配對為標準數值,重複上述。第三步驟建立一個能以正確配對特徵點自動變化的範圍,將其均勻分類並篩選合適特徵點,最後將最合適的組合進行仿射轉換,找到最適合的轉換參數。我們將此方法與當今衛星影像套合的方法進行比較,實驗結果顯示本方法可以得到精確且節省時間的效果。該策略可應用在多種衛星影像,例如:城市、河流、山谷、海岸,觀察城市發展、河流侵蝕變化和海平面上升。 | zh_TW |
dc.description.abstract | Image registration is defined as the same object of two different sources alignment by some kind of image transformation. Since satellite imagery has different image types and complex image scenes for a variety of measurement observation, developing automatic image registration methods for satellite imagery is still a big challenge. This thesis proposes a fast and accurate method to achieve automatic satellite image registration, which is composed of three major steps:the first step is to use the improved scale-invariant feature transform(SIFT)method, in which bilinear interpolation resampling is adopted to solve the original resampling problem due to rotation and displacement. Then, we normalize the feature description values to make two feature point sets more precise and robust. The second step is to remove the misjudgment of the feature point pairs. We use a random sampling combination algorithm to sample feature points. On the one hand, when the number of successful inspection is greater than half of the current sampling number after reaching the basic sampling number. It is classified as correct pairing. Doing this stop the iteration earlier and speed up the whole process. On the other hand, if the number of correct pairs is not enough, we repeat the above step with the current correct pairing as the standard value. The third step is to build a measurement domain that automatically changes with respect to the correct pairing feature points. We make them evenly and filter the appropriate feature points. Finally, we extract the most suitable combination to find the most suitable conversion parameters. By comparing this new approach with other satellite image registration methods, it is suggested that our method is precise and time-saving that can be applied to a variety of satellite imagery, such as cities, rivers, valleys, and coasts. It can be used to observe urban development, changes in river erosion, and rise of the sea level. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T08:07:04Z (GMT). No. of bitstreams: 1 ntu-108-R06525056-1.pdf: 5589922 bytes, checksum: 2ae8842bf08f3205fff9d2db57aa2d1f (MD5) Previous issue date: 2019 | en |
dc.description.tableofcontents | 致謝...............................................................................................................................i
中文摘要......................................................................................................................ii ABSTRACT ................................................................................................................iii 目錄.............................................................................................................................. v 圖目錄.......................................................................................................................viii 表目錄.......................................................................................................................... x 第 1 章 緒論 ................................................................................................................ 1 1.1 研究背景.................................................................................................... 1 1.2 研究動機.................................................................................................... 2 1.3 論文架構.................................................................................................... 2 第 2 章 相關理論 ............................................................................................... 4 2.1 遙測影像.................................................................................................... 4 2.2 影像資料格式............................................................................................ 5 2.3 影像套合.................................................................................................... 6 2.3.1 影像套合基本概念 ........................................................................... 6 2.3.2 特徵點偵測....................................................................................... 6 2.3.3 特徵點描述訊息............................................................................... 8 2.3.4 仿射轉換(Affine transformation)....................................................... 8 2.3.5 雙線性內插法(Bilinear interpolation) ............................................. 11 2.4 尺度不變特徵轉換(SIFT)........................................................................ 12 2.4.1 高斯濾波器..................................................................................... 12 2.4.2 高斯差異(Difference of Gaussian)................................................... 14 2.4.3 特徵點偵測..................................................................................... 15 2.4.4 消除邊緣響應................................................................................. 16 2.4.5 方向定位與特徵點描述.................................................................. 18 2.4.6 特徵點匹配..................................................................................... 20 2.5 影像套合效果評估標準........................................................................... 20 2.5.1 互資訊............................................................................................. 20 2.5.2 相關係數......................................................................................... 22 2.5.3 均方根誤差..................................................................................... 23 第 3 章 研究設計與方法.................................................................................. 24 3.1 流程圖...................................................................................................... 24 3.2 修正 SIFT 方法........................................................................................ 26 3.3 特徵值描述正規化 .................................................................................. 29 3.4 匹配錯誤消除.......................................................................................... 30 3.5 特徵點分布.............................................................................................. 34 3.6 仿射轉換.................................................................................................. 36 第 4 章 實驗與結果 ......................................................................................... 37 4.1 實驗說明.................................................................................................. 37 4.2 特徵點匹配的相對距離比例................................................................... 39 4.3 特徵點分布均勻性 .................................................................................. 41 4.4 衛星影像的影像套合............................................................................... 43 4.5 影像套合成效統計 .................................................................................. 44 4.6 多光譜衛星影像套合............................................................................... 47 第 5 章 結論與未來展望.................................................................................. 53 附錄 A 多時影像資料集 .......................................................................................... 55 附錄 B RMSE 與各種方法的最佳參數 ................................................................. 58 參考文獻.................................................................................................................... 63 | |
dc.language.iso | zh-TW | |
dc.title | 提升特徵點配對精準度於衛星影像套合 | zh_TW |
dc.title | Improving Feature Point Matching Accuracy for Satellite Image Registration | en |
dc.type | Thesis | |
dc.date.schoolyear | 107-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 黃乾綱(Chien-Kang Huang),張瑞益(Ray-I Chang),戴璽恆(Hsi-Heng Dai) | |
dc.subject.keyword | 遙測影像,影像套合,尺度不變特徵轉換,仿射轉換, | zh_TW |
dc.subject.keyword | remote sensing image,image registration,SIFT,affine transformation, | en |
dc.relation.page | 67 | |
dc.identifier.doi | 10.6342/NTU201903946 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2019-08-19 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 工程科學及海洋工程學研究所 | zh_TW |
顯示於系所單位: | 工程科學及海洋工程學系 |
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