ENGLISH

14卷/4期

14卷/4期

華藝線上圖書館

Pages:

255-275

論文名稱

房屋模型面與空載影像之套合

Title

Spatial Registration between Building Facets and Aerial Images

作者

陳良健,江孟璁

Author

Liang-Chien Chen ,Meng-Tsung Chiang

中文摘要

本研究利用傳統空照影像與傾斜攝影直升機影像,對現有房屋模型之牆面及屋頂面進行套合。處理重點除幾何對位外,並偵測牆面及屋頂面之遮蔽區,且對遮蔽區域以多視角影像及影像修補技術加以補償。牆面部分所使用之影像,是基於影像傾斜攝影概念。對欲處理之目標牆面,應以影像傾斜攝影角度最大為優先,如此可得到影像解析度較佳之牆面影像,但相對的,牆面被其他建築物遮蔽的情況也較嚴重;本研究的重點,即為於這些影像中,找到最佳化的組合。屋頂面部分,則以垂直攝影影像,可得解析度較佳之屋頂面,在此以真實正射之概念進行影像套合。成果顯示於套合幾何對位上滿足視覺化之要求。

Abstract

This research registers aerial photos and oblique helicopter images onto building facades. In which, building roofs and walls are to be treated. In addition to geometric registration, the proposed method detects hidden areas for roofs and walls, then compensates them with multi-view images and inpainting techniques. The wall images that we choose are based on oblique photography. For the target wall, we should select the largest oblique angle for the prior image in order to get better resolution. However, the occlusion problem by neighboring buildings is more serious. It is the major task of this study to select the optimal combination of images. For the roof, we use the vertical photos to obtain better resolution. The essence of the step is to register the roof surface with images. The results show high fidelity in visualization.

關鍵字

空照影像、房屋模型、遮蔽區、傾斜攝影、影像套合

Keywords

Aerial images, Building models, Occlusion detection, Oblique photogrammetry, Image registration

附件檔名

華芸線上圖書館

N / A

備註說明

200912-14-4-255-275

Pages:

237-253

論文名稱

整合式光學衛星影像區域平差

Title

Integrated Adjustment for Optical Satellite Images

作者

張紋綺,陳良健

Author

Wen-Chi Chang,Liang-Chien Chen

中文摘要

衛星影像幾何處理可分為嚴密幾何模式和有理函數模式。嚴密幾何模式又可細分為光束法及直接地理對位,其中的直接地理對位是以星曆資料為基礎,需較佳的起始值,所以對地面控制點的需求較少。而有理函數模式是使用兩個多項式的比值來建立物空間與像空間的轉換關係,標準化的數學形式較嚴密幾何模式簡易。實際的應用上,有些衛星公司僅提供有理函數轉換係數,有些衛星公司僅提供星曆資料。當兩類的衛星影像要進行整體平差時,則需考量異質模式間之整體平差,因此嚴密幾何模式與有理函數模式有其整合之必要性。本研究結合直接地理對位及有理函數模式進行整體平差。研究重點為兩種異質數學模式間之整合處理。主要工作項目包括直接地理對位及有理函數模式之建立,配合數值地形模型進行高程控制,並以最小二乘配置法補償局部系統誤差。實驗內容分別測試本文提出之異質整合模式與其它同質性整體平差之方法之比較、分析連結點數的增加對於成果之影響,與針對不同空間解析度之影像進行整合處理與分析。精度評估分為兩部份,分別為地面定位坐標誤差和影像間之相對偏移量。實驗成果顯示,本研究所提出之異質整合模式可有效改善影像間幾何一致性。

Abstract

The geometric modeling may be divided into two categories, namely, rigorous sensor model (RSM) and rational function model (RFM). The RSM contains Bundle Adjustment and Direct Georeferencing. Actually, some satellite companies provide the Rational Polynomial Coefficients (RPC) instead of the ephemeris data. Some others are on the contrary. The adjustment of the heterogeneous models between RSM and RFM should be integrated when the two types of images are employed.This paper combines Direct Georeferencing and RFM for multi-sensor block adjustment. Two heterogeneous models using Digital Elevation Model (DEM) as elevation control are integrated. The major works of the proposed schemes include (1) building up Direct Georeferencing mathematics, (2) setting up RFM, and (3) compensating the local systematic errors by least squares collocation. The experiments test the different geometric models, different numbers of tie points, and the integration of multi-resolution images. The validation includes two parts: absolute accuracy and relative discrepancy. Experimental results indicate that the proposed method can improve the relative discrepancy.

關鍵字

直接地理對位、有理函數模式、區域平差、最小二乘配置法

Keywords

Direct Georeferencing, Rational Function Model, Block Adjustment, Least Squares Collocation.

附件檔名

華芸線上圖書館

N / A

備註說明

200912-14-4-237-253

Pages:

277-286

論文名稱

演算法LLL應用於GNSS相位模稜快速求解

Title

Quick GNSS Carrier-phase Ambiguity Resolution Based on the LLL Algorithm

作者

陳揚仁,吳究,謝吉修

Author

Yang-Zen Chen ,Joz Wu,Chi-Hsiu Hsieh

中文摘要

一般而言,全球導航衛星系統載波相位之定位精度較電碼定位高,利用載波相位觀測量進行衛星測量求解位置時,如何快速得到正確的整數相位模稜值,是求解精度與效率的關鍵。但是參數間彼此高相關,會使這個目標變的困難。通常這個問題可藉由衛星之間的幾何構形改變而獲得改善,但是相對的需要花費更多的時間進行觀測。LLL演算法是一種將問題由高相關域轉換至低相關域的技術。LLL利用Gram-Schmidt正交變換產生一具備對角優勢之協方差矩陣,使得數學上的變換能夠達成與幾何變換相同的效果。應用具備對角優勢之協方差矩陣可大幅減少整數相位模稜的候選解。最後將候選解逐一代入觀測式中重新進行平差演算,求取一殘差二次形為最小之解。

Abstract

Generally, the global navigation satellite system carrier-phase is more accurate then the pseudorange. The key point is how to obtain the correct integer ambiguity quickly and efficiently, while using carrier-phase for positioning. However the high correlation between parameters makes it to be difficult. The problem can be improved by the changing of the geometric of satellites. But it needs longer observation time to reach.The LLL algorithm is a technique mapping the parameters from a higher correlation space to a lower correlation space. The LLL algorithm uses the Gram-Schmidt orthogonalization to produce the diagonal covariance matrix. The effects of mathematics changing and the geometric changing can be the same. The number of candidates for integral ambiguity can reduce by using the diagonal covariance matrix. Final, the candidates are inserted into the observation equations to determine the solution again. It is believed that the integer candidate which produces the smallest sum of squares of the residual is the most likely solution we want

關鍵字

相位模稜、高相關、正交化

Keywords

Ambiguity, High correlation, orthogonalization

附件檔名

華芸線上圖書館

N / A

備註說明

200912-14-4-277-286

Pages:

287-302

論文名稱

應用非監督模式分類河川污染空間分佈之研究

Title

Using Unsupervised Method To Classify the Space of River Pollution in the Image of the Satellites

作者

施明倫,楊政儒,顏可翰

Author

Min-Luen Shih,Jeng-Ru Yang ,Ke-Han Yan

中文摘要

本研究使用自行開發之非監督式兩階段模糊及機率模式作為河川空間污染分類的研究,目前水質遙測分類大都使用監督模式,但監督式模式前提需建構一個多樣且代表性的學習樣本,相對的非監督模式毋需準備學習樣本,只需要少部分現場水質污染監測分類值作為最終判斷的參考,且少了監督模式學習建模之複雜性;本研究模式亦改善傳統非監督模式需要預設資料分類數的缺點,模式採自動最佳化分類結果,因河川污染是由多種不同水質綜合而成,分類數也隨不同河川有所差異,故不預設模式分類數,藉最佳化分類衛星遙測影像河川水體之污染情形。另外為提高對河川水質污染分類之精確度,透過篩選輸入最佳光譜變量組合,可進一步建立一套遙測河川表面水質空間污染的分類系統。

Abstract

This story uses a two unsupervised fuzzy and probabilistic clustering method in order to research how predict the space of rivers is polluted. The river pollution includes many kinds of different water quality. But it is to need to possess various and representative study sample to utilize the supervised type to classify. Unsupervised method does not needing to study samples, but need local value as monitoring and classifying the basis finally. This method improves many traditional unsupervised methods that have been set up the number of clusters, and the automatic optimization classification. It is classing the pollution of river in the image of the satellites. In addition improve the accuracy predicted to the pollution of river, input the best variable association that is screened, in order to set up the prediction system that the space of river pollution in the image of the satellites.

關鍵字

衛星遙測、兩階段模糊機率非監督模式、最佳化分類

Keywords

remote sensing, two unsupervised fuzzy and probabilistic clustering method,feature selection

附件檔名

華芸線上圖書館

N / A

備註說明

200912-14-4-287-302

Pages:

303-316

論文名稱

高光譜影像立方體於特徵空間之三維紋理計算

Title

Three Dimensional Texture Computation in Feature Space for Hyperspectral Image Cubes

作者

賴哲儇,蔡富安

Author

Jhe-Syuan Lai , Fu-an Tsai

中文摘要

本研究提出灰階共生張量場概念,單次記錄高光譜影像立方體中三個像元的灰階出現頻率,並進行三階統計指標運算,以期產生更佳的三維特徵萃取。再者,本文研發新的演算法訂定三維紋理計算之視窗(核)尺寸,以光譜分離度分析,求得最能區別各類別組的波長取樣間距,做為光譜方向的視窗尺寸,並結合半變異元分析決定空間方向的視窗尺寸,增加三維紋理計算的分類精度。研究成果顯示,以分離度分析配合半變異元分析決定的視窗尺寸,可產生較佳的三維紋理計算成果。此外,灰階共生張量場在多數的統計指標能有效地提升特徵萃取與地物分類的成果。

Abstract

This study extended traditional GLCM (Gray Level Co-occurrence Matrix) texture analysis to a tensor field (Gray Level Co-occurrence Tensor Field, GLCTF) that uses three voxels from hyperspectral image cubes, and utilized third order statistics to extract subtle features from hyperspectral datasets. This paper also developed an algorithm based on spectral separability measures to identity the best sampling intervals of class pairs as the appropriate kernel sizes in the spectral dimension for GLCTF computation. Combining with spatial window sizes determined from semi-variance analysis, it is more appropriate to determine the size of a three-dimensional moving box for GLCTF computation to extract separable features from hyperspectral datasets for classification. Experimental results demonstrated in this paper indicate that coupling separability measures and semi-variance analysis can determine more appropriate kernel sizes for 3D texture computation. In addition, GLCTF in most indexes has better classification results in the test cases.

關鍵字

紋理共生矩陣、光譜分離度分析、半變異元分析、灰階共生張量場

Keywords

Texture Analysis, GLCM, Separability Measures, Semi-Variance Analysis, GLCTF

附件檔名

華芸線上圖書館

N / A

備註說明

200912-14-4-303-316

Pages:

317-332

論文名稱

利用MODIS影像推估台灣沿岸海水透視度

Title

Using MODIS Imagery to Estimate Secchi Depth Turbidity of Taiwan Coastal Water

作者

王驥魁,康哲銓

Author

Chi-Kuei Wang , Che-Chuan Kang

中文摘要

海水透視度為影響透水光達系統(Bathymetry Lidar)的主因,若能在施測時依據海水透視度進行飛航規劃,則可有效提升整體施測效益。沙奇盤深度常用於量測海水透視度,因此本文利用Aqua MODIS衛星影像輔以現地蒐集之沙奇盤、透光度計與背向散射計等65點外業船測資料,其中將船測資料同步之19個衛星影像,分別利用488nm與532nm兩個波段,搭配三種不同沙奇盤深度與海水光學性質的關係式,進行沙奇盤深度與船測值分析比較,顯示532nm波段的推估結果優於488nm波段,並由三種關係式中確認誤差最小的關係式。分析2004年至2007年的MODIS影像資料,顯示台灣海域之沙奇盤深度與海水光學性質皆有年週期變化,可作為透水光達評估作業之參考依據。

Abstract

Secchi depth affects the performance of the airborne bathymetric lidar system. Therefore, the operation efficiency can be benefited if the secchi depth turbidity can be obtained in advance. In this research, the MODIS sensor onboard Aqua satellite is used due to its ability to provide extensive temporal and spatial imagery. A total of 65 depth profiles are collected including instruments of Secchi Disk, AC-9, and Hydroscat-6 from May, 2007 to May, 2008. Within that dataset, a total of 19 profiles were collected concurrent with Aqua MODIS overpass. There have been reports of three relationships between optical properties and secchi depth based on either 488 nm or 532 nm. Investigations are made to compare which combination of optical relationship and wavelength is most reliable. Temporal analysis of MODIS images reveal a yearly variation of Secchi depth values, which is important information for airborne bathymetric lidar flight planning.

關鍵字

透水光達、MODIS、沙奇盤深度、海水透視度

Keywords

Airborne Bathymetric Lidar, MODIS, Secchi Depth, Water Clarity

附件檔名

華芸線上圖書館

N / A

備註說明

200912-14-4-317-332

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