查詢結果分析
相關文獻
- 光達點雲平面特徵自動化匹配於航帶平差之應用
- 暴雨型崩塌地自動判釋及特徵分析之研究
- 利用類神經網路方法於高解析衛星影像及地形資料之崩塌地辨識--以九份二山為例
- Neural Network Procedures for Taguchi's Dynamic Problems
- A Fast and Efficient Competitive Learning Design Algorithm Based on Weight Vector Training in Transform Domain
- 專家系統振動訊號圖型判別之研究
- 反傳遞模糊類神經網路於流量推估之應用
- 類神經網路(Neural Networks)的種類及其在影像處理上的應用
- C++Fuzzy類神經網路物件導向發展系統之建立
- 臺灣汽保費率之估計--對數線性費率模式與類神經網路之比較
頁籤選單縮合
題 名 | 光達點雲平面特徵自動化匹配於航帶平差之應用=Automated Planar Feature Matching for Adjustment of Lidar Strips |
---|---|
作 者 | 尤瑞哲; 王偉立; | 書刊名 | 航測及遙測學刊 |
卷 期 | 14:3 2009.09[民98.09] |
頁 次 | 頁185-199 |
分類號 | 440.98 |
關鍵詞 | 張量投票; 類神經網路; 航帶平差; 空載光達; Tensor voting; Artificial neural network; Strip adjustment; Airborne lidar; |
語 文 | 中文(Chinese) |
中文摘要 | 空載光達的系統性誤差會造成相鄰航帶點位高程偏差,通常應用航帶平差方法來減低系統性誤差的影響。使用這種方法時,必須在不同航帶找出對應區域或連結點的位置。一般以人工選取的方式決定對應區域或連結點的位置,而人工選取的方式費工又費時。本文提出一套自動化選取對應區域或連結點的方法:首先以張量投票法自動偵測光達平面特徵;其次計算同一航帶內所萃取出的平面之位相關係,並將具有相似位相關係的平面以二階段的類神經網路演算法進行匹配,同時提出以二分樹法來提高匹配的正確率;最後再將匹配後得到的共軛平面之重心坐標視為連結點進行航帶平差。本法的好處是連結點的選取工作可以自動化地執行。航帶平差的實驗結果顯示:本文所提出的自動化匹配對應平面區域的方法對於改善空載光達高程精度是相當可行的。 |
英文摘要 | Systematic errors of airborne Lidar data cause elevation offset of point clouds. Strip adjustment is one of the ways to reduce systematic errors. Using strip adjustment, the locations of conjugate blocks or tie points have to be detected first and they usually be manually selected and decided with laborious and time-consuming efforts. The purpose of this study is to develop a method for automatically selecting conjugate blocks or tie points. In this article, the tensor voting method is adopted for the extraction of planar features from Lidar data and an artificial neural network method is applied to match the planes with similar topologic properties. The Bintree method is used for increasing the success rate of classification based on the artificial neural network algorithm. The gravity centers of matched conjugate planes are regarded as tie points for strip adjustments in this study. The advantage of the current algorithm is that the choice of tie points can be executed automatically. The results of experiments of strip adjustments show the feasibility of our algorithm to improve the height accuracy of airborne Lidar data. |
本系統中英文摘要資訊取自各篇刊載內容。