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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/64900


    Title: 航照影像特徵輔助之半全域匹配 於數值地表模型建立
    Authors: 藍裕翔;Lan,Yu-xiang
    Contributors: 土木工程學系
    Keywords: 數值地表模型;航空影像;密匹配;半全域匹配法;中左右視窗匹配法;物空間導向匹配;Digital Surface Model;Aerial Image;Dense Matching;Semi-Global Matching;Central-Left-Right Matching;Object-Based Image Matching
    Date: 2014-07-30
    Issue Date: 2014-10-15 14:33:07 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 數值地表模型描述地形與地物之表面,是空間資訊處理中目標物三維重建之重要資料。考量其重要性,本研究針對建物區使用航照影像建構數值地表模型。文中就數值地表模型建構之兩個重要工作: (1) 獲取點雲資料及 (2) 模型化,提出方法及處理程序。

    獲取資料的部分,使用多影像匹配技術來獲取三維點雲。因點雲的密度將影響數值地表模型細節之重建,故本研究採用密匹配的方式以獲取高密度三維點雲。常用之局部單目標窗匹配法中僅考慮匹配點附近的局部相似性,較缺乏區域性的連結,若能考慮區域相似性則能提高匹配結果的整體性。半全域法評估多個方向路徑上各點的相似性,並加入平滑度限制,同時考量區域及局部的影像特性,可望得到較穩定的結果,故使用於本研究中。然而平滑度限制在高程不連續處仍可能造成匹配不穩定。中左右之多視窗匹配方式考慮局部特徵條件,可望改善匹配結果。因此本研究結合半全域法與中左右視窗匹配法,可在建物邊緣處提升半全域法的匹配品質。相較於純像空間之匹配法,物空間導向之影像匹配從地元出發,連結對應之像點,並計算與主影像間之相似性。此種作法可處理不同解析度之影像,且利於多張影像匹配,故將整合於提出之匹配程序。

    模型化的程序中,應該考慮建物邊緣的處理。影像中特徵線提供了良好的線索以找尋房屋邊緣。因此透過三維點雲與影像上的特徵線分析以判定房屋之輪廓。本研究萃取房屋輪廓,並以房屋輪廓當作約制精化數值地表模型。實驗成果顯示,結合半全域匹配法與中左右視窗匹配法可以達到互補之效果並提升匹配品質,另外以線特徵為約制精化模型的方法可以增進最後模型成果的品質。
    ;Digital Surface Model (DSM), which describes the surface topography, is an important data source in geoinformatic applications. Considering its importance, this research uses aerial images to construct DSM for building areas. This study includes two major works:(1) point cloud generation and (2) surface modeling for DSM reconstruction.

    It is a practical way to generate 3D point clouds by matching multiple images. Because the density of 3D points clouds may influence the constructed details of DSM, this research employs dense matching method to generate 3D points clouds. Matching methods using local single target window only consider local similarity near the matching points. It lacks global links to other pixels. The matching results could be improved, provided that the global similarity is considered. Semi-Global Matching (SGM) considers connected paths with smoothness constraints and combines local and global image information so it can get stable results. However, smoothness constraint might be unable to cope with the matching ambiguity in the area with surface discontinuity. Central-Left-Right Matching (CLRM), on the other hand, considers local feature constraint using multi-windows to increase matching quality around feature regions. Thus, the integration of CLR and SGM is proposed in this investigation. Object-based image matching starts from a groundel to connect related image pixels. Because object-based image matching strategy can connect multiple images with different image resolutions, it will be employed in this research.

    In the DSM modeling, surface discontinuity should be taken into account. Feature lines in the images provide a valuable clue for the detection of possible surface discontinuity such as at building boundaries. Thus, 3D break lines might be determined by incorporating the point clouds and image feature lines. In this research, we extract building boundaries followed by the inclusion of those boundary lines as constraints to shape the DSM. The experimental results indicate that the integration of CLR and SGM can increase the quality of image matching. In addition, the proposed method that uses feature constraint to shape DSM can improve the quality of the generated DSM.
    Appears in Collections:[土木工程研究所] 博碩士論文

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