ENGLISH

13卷/3期

13卷/3期

華藝線上圖書館

Pages:

159-168

論文名稱

結合多元資料重建三維房屋模型

Title

Integrating Multi-source Data for the Generation of 3-D Building Models

作者

陳良健, 李唐宇

Author

Liang-Chien Chen,Tang-Yu Li

中文摘要

三維房屋模型的建立在數碼城市中不可或缺。本研究以資訊融合方式,結合向量圖、空載光達資料 以及航照資料,重建三維房屋模型。重建的重點包括圓弧屋頂和非圓弧屋頂之房屋。研究中使用向量資 料提供房屋外部輪廓,因此研究重點為房屋模型重建。由於圓弧屋頂之房屋在影像上並無明顯特徵,因 此研究以空載光達資料之三維資訊來描述圓弧屋頂。而為了彌補光達點雲密度可能不足之情形,研究使 用航照影像獲取非圓弧形屋中平頂屋內部結構直線段。研究步驟,首先對三種資料分別進行前處理的作 業,接著萃取房屋內部之光達點雲,由不同的面方程式進行擬合,將不同之屋頂形狀分類。研究中以平 面方程式所擬合的小單元描述圓弧頂房屋,非圓弧頂者,山型屋以面相交方式求取屋脊線,平頂屋部份 結合空載光達資料與影像偵測階梯線。最後利用分割-合併-模塑方法模塑產生房屋模型。本研究測試區位 於新竹科學園區。向量圖比例尺為1:1000,空載光達資料點雲密度為1.5pts/m2,航照影像之空間解析力 為0.12 m。研究成果顯示,屋頂面分類成功率可達80%,模型重建正確率為85%。房屋輪廓部分均方根 誤差於X 方向為0.51 m,Y 方向為0.41 m,模塑誤差為0.19 m。

Abstract

Three dimensional building models are the indispensable component in the cyber city. This investigation integrates 2-D maps, LIDAR data, and aerial images for building modeling. This research handles flat, gable, and cambered roofs. Vector maps are used to locate the building boundaries in this research. Since a cambered roof does not have significant features in the image space, we use the LIDAR point clouds to model it. Because the density of the LIDAR point clouds might not be sufficient to reconstruct the internal facets of buildings, we employ aerial images. In the first step, the data preprocessing encloses the polylines of the maps then extract the point clouds that belong to a building. After filtering the point clouds, we fit the data by different surface functions. Through the roof hypothesis by employing point clouds, the camber roofs are parameterized. For non-camber roofs, the ridges of gable roofs will be intercepted by the two inclined planes. The step-edges of flat roofs are obtained by combining point clouds and image features. Then the lines are projected to the object space by ray-tracing. Finally, we shape the models by SMS method. The test site is in the Industrial Technology Research Institute of Hsin-chu. The vector maps are with a scale of 1:1,000. The point density of LIDAR data is 1.5 points/m2, and the spatial resolution of aerial image is 0.12 m. The result indicates the successful rate is 80% in building classification while the fully reconstruction rate is 85%. The RMSE of building boundaries are 0.51 m and 0.41 m in X and Y directions, respectively. The shaping error is 0.19 m.

關鍵字

光達、航照影像、向量圖、模型重建、房屋模型

Keywords

LIDAR, aerial image, 2D map, building reconstruction, building model

附件檔名

華芸線上圖書館

N / A

備註說明

200809-3-1-159-168

Pages:

169-182

論文名稱

以三維直線特徵進行地面光達點雲套合

Title

Registration of Terrestrial LidAR Point Clouds by Means of 3D Line Features

作者

趙鍵哲,莊子毅

Author

Jen-Jer Jaw 1,Tzu-Yi Chuang

中文摘要

本研究針對地面光達點雲資料以三維直線特徵為基礎進行特徵萃取、特徵匹配及空間相似轉換,以 完成連續測站之點雲資料套合。研究工作內容可分為三個主要發展核心: 三維直線特徵萃取器、三維直 線特徵匹配機制與以三維直線特徵為基礎的點雲套合數學模式。特徵萃取採用影像處理技術由光達點雲 提取三維直線特徵,並以三維直線特徵匹配機制透過幾何約制找尋共軛直線配對,做為點雲資料套合元 件;而以三維直線特徵為基礎的點雲套合模式則以線性模式提供轉換參數之近似解作為非線性嚴密模式 之參數起始值,可避免參數起始值給予問題且減少人為介入;在套合轉換計算上為避免套合轉換誤差累 積,本研究採用同時平差解算(Simultaneous Adjustment)模式。由實驗成果顯示本文所提出以三維直線特 徵為基礎之方法對於具結構物場景確實可有效率地完成地面光達點雲資料套合,而對於其它場景則應可 做為點雲資料套合處理的可能選項。

Abstract

In this paper, the authors elaborate on an innovative approach for registering terrestrial LiDAR point clouds of overlapping scans based on 3D line features. The proposed working scheme consists of three major kernels: a 3D line feature extractor, a 3D line feature matching mechanism, and a mathematical model for simultaneously registering LiDAR point clouds of multi-scans on a 3D line feature basis. The combination of approximate and rigorous transformation models makes fully automatic transformation possible. Besides, the simultaneous adjustment prevents errors from being accumulative among scans. Experiments conducted show the proposed method of employing 3D line features to be a useful alternative or complement to point, surface and other features for LiDAR point clouds registration. It is especially effective in areas rich in man-made structures.

關鍵字

地面光達、三維直線特徵、套合、同時平差解算

Keywords

Terrestrial LiDAR; 3D Line Feature; Registration; Simultaneous Adjustment

附件檔名

華芸線上圖書館

N / A

備註說明

200809-3-1-169-182

Pages:

183-194

論文名稱

多參考站GPS 動態定位演算法之研究

Title

Research on GPS Kinematic Positioning with Multiple Reference Stations

作者

朱康文,吳 究,謝吉修

Author

Kang-Wen Chu ,Joz Wu,Chi-Hsiu Hsieh

中文摘要

中長距離GPS 定位存在與距離相關的各種誤差,如大氣折射,這些誤差使單時刻相位模稜解算成功 率降低,進而影響定位精度。使用多參考站可以模式化參考站與使用者間與距離相關的各種誤差,期望 可以增加使用者的移動距離或提升定位精度。本研究目的在利用已知坐標,找出參考站間的相對對流層 天頂向延遲(Relative Tropospheric Zenith Delay, RTZD),並提供移動站內插改正數,以得到更精確的定位 結果。主要工作分為三個階段:(1)使用虛擬RTZD 觀測方程式,計算參考站間的RTZD;(2)根據參考站 數目,選擇適當的改正面函數;(3)動態定位。本研究方法僅需使用一至三時刻觀測量即可成功獲得定位 整數解,可降低周波脫落或資料中斷影響。實驗結果指出,若能正確求得參考站間RTZD,並使用適當 的內插模式,則可改善定位精度。

Abstract

The distance-dependent GPS errors, notably atmospheric refraction, reduce the success rate of epoch-by-epoch ambiguity resolution, and limit the GPS positioning accuracy, especially for mediumto long-range baselines. Using multiple reference stations to model (or interpolate) the distance-dependent biases between the reference station and a rover can extend the distance or improve the positioning accuracy. The objective of this research is to find out the relative tropospheric zenith delays (RTZD) between different reference stations by using known coordinates and to provide rovers with interpolated corrections for more precise positioning. The project consists of three major steps: (1) finding out the RTZDs between reference stations, (2) modeling the RTZDs; (3) kinematic positioning. In the first step, a pseudo observation equation of RTZD is added in order to reduce the impact of RTZD on ambiguity resolution. In the second step, different model is used according to the numbers of reference stations. These two steps are the emphases of this investigation. The proposed method needs only one to three epochs to resolve ambiguities, so the effects of cycle slip or data gap are not very serious. A multiple reference stations network located in north Taiwan is used in this research. There are six permanent GPS stations in this network. Test result indicates that if the RTZDs between different reference stations can be resolved successfully, and a proper interpolation model is used, it is possible to improve the positioning accuracy.

關鍵字

多參考站、GPS 動態定位、對流層天頂向延遲

Keywords

Multiple reference stations, GPS kinematic positioning, Tropospheric zenith delay

附件檔名

華芸線上圖書館

N / A

備註說明

200809-3-1-183-194

Pages:

195-206

論文名稱

數值高程模型之品質評估

Title

Quality Assessment for Digital Elevation Models

作者

楊善智,曾義星

Author

Shan-Zhi Yang,Yi-Hsing Tseng

中文摘要

數值高程模型 (Digital Elevation Model, DEM) 乃廣泛被使用的空間資料,產製方法相當多元,不同 時期不同方法產製的DEM 品質不一,如何評估其品質是DEM 使用者常面臨的問題。本研究針對不同時 期及不同觀測方法所得之DEM,估計其內部和相對的外部精度品質。內部精度評估以最小二乘估計法為 本,但改善其搜尋計算點方式使其適合於取樣點分佈不均勻的情形。並提出一套相對外部精度評估方法 及流程,透過高程比對分類,探討誤差的類型及可能形成的原因。所發展的理論及方法可用來評估單一 DEM 本身觀測結果之品質,亦有助於分析同區不同來源DEM 間之相對精度品質。實驗資料包含以空載 光達、航測及干涉雷達所生產的DEM,分別測試內部精度評估及相對的外部精度評估。內部精度評估成 果分析合理呈現DEM 因觀測取樣及地形因素影響之內部精度品質,透過DEM 相互比對分析之相對的外 部精度評估成果也能反應相對誤差的模式,得知是否含有平面或高程系統誤差,也能呈現局部之區域性 粗差。

Abstract

Digital Elevation Models (DEMs) are widely used in many spatial information related applications. There are a variety of technologies developed for DEM generation, such as digital photogrammetry, airborne LiDAR and InSAR. However, the procedure from raw data sources to DEM products may involve different types of errors, which determine the DEM quality. Therefore, methods for DEM quality assessment are needed for users. This study proposed two methods to describe DEM quality—interior and exterior relative quality assessment. Instead of whole index of RMSE, the former provides accuracy index of each height point calculated from the raw data to reveal the DEM quality in a local area. Then the later explores the relative errors between DEMs acquired from different sources and times. The two methods provide useful information to DEM quality assessment, which makes a user to realize the quality of acquired DEMs in detail.

關鍵字

數值高程模型、DTM、DEM、精度評估、品質評估

Keywords

DEM, DTM, Quality assessment

附件檔名

華芸線上圖書館

N / A

備註說明

200809-3-1-195-206

Pages:

207-217

論文名稱

應用小波神經網路於高光譜影像分類

Title

Wavelet Networks For Hyperpsectral Image Classification

作者

楊琇涵,徐百輝

Author

Hsiu-Han Yang, Pai-Hui Hsu

中文摘要

由於高光譜影像具有高維度資料的特性,在有限訓練樣本的情況下,傳統以統計參數為基 礎的影像分類法並無法直接適用。為了降低維度以解決樣本量不足的問題,在分類前先進行光 譜特徵萃取是最常用的方法。過去的研究指出以小波轉換為基礎的小波特徵萃取能有效地萃取 出對高光譜影像分類有用的特徵,然而在固定的尺度、平移參數下,作為特徵的小波係數並無 法依資料類別的特性而進行調整。本研究提出以小波神經網路為基礎的分類器,其同時整合神 經網路的訓練、分類以及小波特徵萃取,在訓練神經網路的過程中,同時動態調整小波轉換中 的尺度、平移參數,並將神經網路中的權值最佳化,達到特徵萃取及分類的效果。由於訓練後 小波神經網路的小波係數是依照各類別訓練樣本的特性而調整,作為分類的特徵時,可提高各 類別的分辨力。實驗結果顯示小波神經網路確實能提高小波特徵萃取的分類精度,且除了訓練 樣本外,小波神經網路分類法幾乎不需要其他的先驗統計資訊,更增加了該分類法應用上的方 便性。

Abstract

Because of the high dimensionality of hyperspectral images, traditional statistics-based classifiers cannot be directly used for the hyperspectral image classification with limited training samples. The commonly used method to solve this problem is dimensionality reduction. Several research works have proven that wavelet transform provides an appropriate and effective tool for spectral feature extraction. Also, the researches about back-propagation neural networks for image classification have been investigated. In this study, wavelet networks is proposed for hyperspectral image classification. With wavelet networks, the important task of feature extraction is performed with wavelet transform, whereas classification is carried out by back-propagation neural networks. Both the position and the dilation parameters of the wavelets are optimized as well as the weights of the network during the training phase. The experiment results suggested that wavelet networks can be a useful and effective classifier for hyperspectral image classification.

關鍵字

小波神經網路、高光譜影像、特徵萃取

Keywords

Wavelet networks, Hyperspectral, Feature Extraction

附件檔名

華芸線上圖書館

N / A

備註說明

200809-3-1-219-230

Pages:

219-230

論文名稱

空照數位像機拍攝高重疊影像匹配高密度點雲

Title

3D Point Cloud Determination by Using Highly Overlapping Images Taken from Digital Aerial Cameras

作者

陳英煥, 蔡展榮

Author

Ying-Huan Chen,Jaan-Rong Tsay

中文摘要

空照數位像機可拍攝高前後重疊率80% ~ 90%的空照影像,大幅減少影像遮蔽區,在航空攝影測量 上,高重疊的空照數位影像對於自動化特徵點萃取、追蹤、匹配有其良好的應用潛力。 本文運用光流迭代法在30 個像元以內可以成功追蹤同名像點的能力,針對現今高重疊率空照數位影 像,設計出一套自動化萃取大量特徵點並加以追蹤、匹配其同名點群的方法,實驗成果驗證這一個新方 法確實可以匹配出平均約1.5 平方公尺(約9 x 9 個像元)便有一個匹配點(本文的實驗影像的一個像元 大小對應於地面是0.13m x 0.13m)的高密度點雲,而傳統航空攝影測量中不易產生連結點的區域,如遮 蔽區、陰影區、樹表面等也可因此大幅提高匹配點密度,以本文遮蔽區為例,平均約6.8 平方公尺(約 20 x 20 個像元)便有一個匹配點,樹表面平均約0.2 平方公尺(約3 x 3 個像元)便有一個匹配點。使用 空中三角測量平差法來檢核新方法匹配點的正確性,此法追蹤匹配成果輸入空三計算,共6 張影像7473 個連結點,僅有50 個錯誤點,正確率達99.3%。 此法成功匹配出高密度的大量三維點雲,可以多張影像立體判讀顯示並檢核之,具有多餘觀測、可 互相檢核,大幅提升可靠度,可供後續各式的應用,例如求定數值地形模型、三維城市建模、重建樹木 表面模型。

Abstract

Digital aerial cameras can take highly overlapping aerial images with the end lap percentage of about 85% ~ 90%. These images have less occlusion areas. For aerial photogrammetry, such aerial images possess a good application potential for automatic extraction, tracking and matching of feature points. This paper utilizes the successful tracking ability of the iterated optical flow approach within the tracking distance of less than 30 pixels, and develops a new method for image matching and determining the corresponding 3D points. Test results verify that it can determine about one point per 1.5m2 (≈9×9pixels). Also, it can automatically determine one point per 6.8m2 (≈20×20pixels) and one point per 0.2m2 (≈3×3pixels) in occlusion and tree areas, respectively. Moreover, those matched points are checked by aero triangulation. For example, totally 7473 tie points on 6 images are regarded to be successfully matched from 6 overlapping images in a strip by the proposed method. Only 50 tie points are mismatched points detected by reliability theory. In other word, there is about 99.3% of the matched points which are correct and determined by the method. This study proposes the new method for image matching using highly overlapping aerial images. It provides more redundancy and more reliable matching results than the ones done by traditional stereo pair. A huge number of matched points can be then applied to determine a dense cloud of 3D object points for later applications such as DTM determination and 3D cyber city modeling.

關鍵字

空照數位像機、高重疊影像、影像追蹤匹配

Keywords

digital aerial camera, highly overlapping images, image tracking and matching

附件檔名

華芸線上圖書館

N / A

備註說明

N / A

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