ENGLISH

12卷/4期

12卷/4期

華藝線上圖書館

Pages:

283-290

論文名稱

基於空間渾沌模型之合成孔徑雷達影像變遷偵測應用於受災範圍估測

Title

Change Detections from SAR Images for Damage Estimation Based on a Spatial Chaotic Model

作者

曾裕強,邱順興

Author

Yu-Chang Tzeng,Shun-Hsing Chiu

中文摘要

合成孔徑雷達因其可全天候地提供影像,故特別適合用以監測災害事件。當災害發生時,其所影響 之區域在合成孔徑雷達影像上會產生很大的改變。因此,可將變遷偵測(change detection)技術應用於合成 孔徑雷達影像,以估計災害發生所影響之範圍。然而,合成孔徑雷達影像因受斑駁雜訊的影響,使得以 合成孔徑雷達影像進行變遷偵測非常困難。斑駁雜訊看起來雖然像是雜訊,但實際上也是合成孔徑雷達 自然所產生的訊號。理論上,合成孔徑雷達訊號可用混沌現象來描述,因其是由在同一個像素內所產生 的許多散射訊號以同調相加方式產生。因此,斑駁雜訊可以一空間渾沌模型(spatial chaotic model)來表示, 並以碎形維度(fractal dimension)來描述其特性。基於空間渾沌模型,本論文提出一簡化的合成孔徑雷達影 像變遷偵測流程,並以實際發生之水災事件為測試例,將此一方法應用於受水災影響範圍之估測。實驗 結果顯示,本論文所提出之方法,是利用合成孔徑雷達影像以估測水災影響範圍的一個非常有實用且有 效率的工具。

Abstract

Because of its all-weather and all-time characteristics, SAR image is particularly effective to monitor disaster events. When a disaster occurs, the image acquired from a SAR sensor changes dramatically. As a result, damage estimation for natural and human-made disasters from SAR images can be achieved by applying a change detection technique. However, it is very difficult to detect changes in SAR images because of the speckle noise in nature. Theoretically, SAR signal can be characterized as a chaotic phenomenon because that the scattering signals within a resolution cell are summed up coherently. Accordingly, SAR signal can be represented by a spatial chaotic model and characterized by its fractal dimension. In this paper, based on the spatial chaotic model, a simplified SAR image change detection procedure is proposed. The proposed method is then applied to estimate the flood-damage area caused by flooding events. Experimental results reveal that the proposed method is an effective and efficient tool for damage estimation from SAR images.

關鍵字

變遷偵測,空間渾沌模型,卡方檢定

Keywords

change detection, spatial chaotic model, fractal dimension

附件檔名

華芸線上圖書館

N / A

備註說明

200712-12-4-283-290

Pages:

291-302

論文名稱

以無參數的分散量為基礎的 k 最近鄰分類器

Title

An Adaptive Nearest Neighbor Classifier Based on Nonparametric Separability

作者

何省華,李政軒,郭伯臣

Author

Hsin-Hua Ho,Cheng-Hsuan Li,Bor-Chen Kuo

中文摘要

k 最近鄰分類器是一個直覺且簡單的分類器。一個好的 k 最近鄰分類器期望類別的條件機率為局部 一致。在本研究裡,我們使用 NWFE 的分散量建立一個有效的量測,進而找出新的鄰近區域。這個新的 測量會將原來用歐式距離建立的鄰近區域延著分散量大的方向收縮且延著分散量小的擴張。而在修正後 的鄰近區域的類別條件機率會趨向於更一致性。在實驗裡,k 最近鄰分類器使用修正後的鄰近區域會比 原來的 k 最近鄰分類器及其它分類器分類效果好。因此,本文所提之方法可改善原始的 k 最近鄰分類 器,而增進分類的效果。

Abstract

A k-nearest-neighbor classifier expects the class conditional probabilities to be locally constant. In this paper, we use the local separability based on nonparametric weighted feature extraction criterion to establish an effective metric for computing a new neighborhood. For each test pattern, the modified neighborhood shrinks in the direction with high separability around this pattern and extends further in the other direction. This new neighborhood can often provide improvement in classification performance. Therefore, any neighborhood-based classifier can be employed by using the modified neighborhood. Then the class conditional probabilities tend to be more homogeneous in the modified neighborhood.

關鍵字

樣式辨識、分類器、k 最近鄰分類器、nonparametric weighted feature extraction

Keywords

pattern recognition, classifier, k-nearest-neighbor (kNN) classifier, nonparametric weighted feature extraction (NWFE)

附件檔名

華芸線上圖書館

N / A

備註說明

200712-12-4-291-302

Pages:

303-317

論文名稱

一個對於高光譜影像的二維模擬退火波段選擇方法

Title

A Two-dimension Simulated Annealing Band Selection Approach for Hyperspectral Imagery

作者

方志鵬,張陽郎,梁文耀,林鈞傑

Author

Jyh-Perng Fang1 Yang-Lang Chang, Wen-Yew Liang, Chun-Chieh Lin

中文摘要

就高光譜影像而言,貪婪模組特徵空間(GME)利用貪婪演算法為基礎群集高度相關的高光譜波段成一個較小 的波段子集合。在本論文中,我們採用模擬退火法取代高光譜影像處理中被採用的GME 方法,模擬退火法在最佳化 方法中通常是一種更有效的探索方法。這篇論文提出一個「二維模擬退火波段選取(2DSABS)」方法,這個方法能 有效地進行高光譜特徵抽取。「二維模擬退火波段選取」以模擬退火演算法為基礎,針對高光譜影像選擇一組非相關 的高光譜波段,同時利用在高光譜影像中不同種類的分離度來降低維度,並且進一步有效地產生一個唯一群集的特 徵空間(CE)。本論文所提出的二維模擬退火波段選取特色有(1)避免轉換資訊成波段的線性組合的偏差值問題,這 是採用傳統的主成份分析方式常見的問題;(2)利用一個簡單的邏輯運算,稱為「CE 特徵維度齊一化轉換」,將不同 種類的資訊混合,形成具有共通特徵波段的群集子集合;(3)提供一個快速的程序,使能同時地選取最有意義的特徵, 並顯著地改善特徵分解計算的複雜性。實驗結果顯示,本論文提出的二維模擬退火波段選取方法有不錯的效率,並 且能夠作為現今特徵抽取演算法中的另一種選擇。

Abstract

For hyperspectral imagery, greedy modular eigenspaces (GME) has been developed by clustering highly correlated hyperspectral bands into a smaller subset of band modular based on greedy algorithm. In this paper, we introduce a simulated annealing mechanism, which is a typical heuristic method in the optimization process, in place of greedy paradigm as adopted in GME approach for hyperspectral imagery. This paper proposes a new method called the two-dimension simulated annealing band selection (2DSABS) for hyperspectral feature extraction. The 2DSABS selects the sets of non-correlated hyperspectral bands for hyperspectral images based on simulated annealing (SA) algorithm while utilizing the inherent separability of different classes in hyperspectral images to reduce dimensionality and further to effectively generate a unique clustered eigenspace (CE) feature. The proposed 2DSABS features can (1) avoid the bias problems of transforming the information into linear combinations of bands as does the traditional principal components analysis (PCA); (2) select each band by a simple logical operation, called CE feature scale uniformity transformation (CE/FSUT), to include different classes into the most common feature clustered subset of bands; (3) provide a fast procedure to simultaneously select the most significant features, and therefore dramatically improve the eigen-decomposition computational complexity. The experimental results show that the proposed 2DSABS approach is effective and can be used as an alternative to the existing feature extraction algorithms.

關鍵字

高光譜、特徵萃取、貪婪模組特徵空間(GME)、模擬退火波段選取(SABS)、群聚特徵模組/特徵維度一致化轉換(CE/FSUT)、主成分分析(PCA)

Keywords

hyperspectral images, feature extraction, greedy modular eigenspaces (GME), simulated annealing band selection (SABS), clustered eigenspace / feature scale uniformity transformation (CE/FSUT), principal component analysis (PCA)

附件檔名

華芸線上圖書館

N / A

備註說明

200712-12-4-303-317

Pages:

319-334

論文名稱

利用MODIS 影像反演嘉義地區水稻田蒸發散量之研究

Title

Using MODIS Imagery to Estimate of Evapotranspiration Over Paddy Field in Chaiyi Plain

作者

余竹樺, 劉說安,張子瑩

Author

Jhu-Hua Yu,Yuei-An Liou,Tzu-Yin Chang

中文摘要

在台灣水資源總量中,農業用水高達其中73%,而又有一半以上的用水量是用於水稻田的灌溉,因 此探討水稻的蒸發散行為,就成為一項重要的課題。估算蒸發散量的方法相當多,利用蒸發皿量測單點 的蒸發散量,或是利用氣象資料經相關公式推估單點的潛勢蒸發散量,常無法反應出區域性的實際狀況, 近年來,由於遙測技術的進步,利用遙測影像推估大面積區域的蒸發行為,就顯得較為重要。 本研究的研究方法就是利用衛星影像配合地面氣象站所量測得的氣象資料(風速、氣溫等),進行地表 熱通量的估計,地表熱通量包括土壤熱通量、可感熱通量及潛熱通量。推估方法基於地表能量平衡演算 法,依據大氣不穩定的修正模式初步推估潛熱通量與可感熱通量,再利用乾、濕控制曲線結合,求出蒸 發散比值,獲得最終的潛熱通量與可感熱通量。 在衛星影像的使用上,則選用中央大學太空及遙測研究中心所提供的MODIS 1D 影像,自行反演地 表參數,以及下載美國USGS 網站所提供的MODIS 地表參數產品,分別輸入模式估算地表熱通量,初步 成果發現,利用MODIS 1D 影像所演算的地表熱通量,較接近實際地面測站的觀測值。因此,本研究則 應用2006 年多張MODIS 1D 的影像,針對當年第一、二期水稻田的潛熱通量的估算,與實地測站比對後, 相關係數可達到0.6。相信未來可長期利用國內所提供的MODIS 1D 影像,以進行嘉義地區水稻田潛熱通 量的監測,期能對稻作的總用水量監控有所幫助。

Abstract

In Taiwan, approximately 73% of the total water resource is been used for agricultural purposes. Among the 73% of agricultural water usage, more than half of the water is used for the paddy rice irrigation. As a result, it is important to evaluate the evapotranspiration characteristic of the paddy rice fields. Traditionally, evapotranspiration is measured by using basin or empirical function with surface meteorological data. However, these methods only measure points and may not effectively address the evapotranspiration over a large spatial domain. To resolve such issue, using remote sensing technology to estimate the evapotranspiration becomes an interest field, as the remote sensing technology has the advantage of acquiring large surface data instantaneously and the data can be used to retrieve surface parameters, as well as thermal prosperities. The research presented here is to use satellite images in conjunction with the in-situ surface meteorological measurement, such as temperature and wind velocity, to estimate the surface heat fluxes that include soil heat flux, sensible heat flux, and latent heat flux. This method is based on surface energy balance to estimate the surface heat fluxes. Once the heat fluxes has been determined, the evaporation then can be derived from radiation and evaporation controlled lines. The satellite data used for this study are the MODIS level 1D image obtaining from CSRSR (Center of Space and Remote Sensing Research), National Central University. In additional, derivative products of the MODIS sensor from USGS/NASA were also obtained for comparative study. The result shows that using MODIS level 1D data as input parameters produces better result and is closer to the ground measurement. Hence, the MODIS level 1D data were used to study the surface heat fluxes of two rice agricultural cycles in 2006. With the correlation coefficient over 0.60, the result shows a potential in estimating the surface heat fluxes of paddy rice fields in Chiayi area, and can be helpful to control the water used to irrigate the paddy rice.

關鍵字

MODIS、蒸發散、水稻田

Keywords

MODIS, Evapotranspiration, Rice paddy

附件檔名

華芸線上圖書館

N / A

備註說明

200712-12-4-319-334

Pages:

335-341

論文名稱

無參數加權特徵萃取對遙測影像目標偵測的應用

Title

Nonparametric Weighted Feature Extraction for Target Detection in Remote Sensing

作者

紀萬偉,任玄

Author

Wan-Wei Chi, Hsuan Ren

中文摘要

線性混合模式(Linear spectral mixture analysis)已經廣泛的被應用在遙測領域上,而最小平方誤差(Least Squares)是眾多有效處理線性混合模式的方法之一。雜訊在線性混合模式中的每一波段不一定是呈現獨 立且相同分佈(Independent and Identical Distributed,(i.i.d)),而雜訊白化最小平方誤差(Noise Whitened Least Squares,(NWLS))藉由雜訊白化處理把雜訊分佈轉換成i.i.d.,並已經被證明能改善傳統最小平方誤差法 的效能。然而,如何去估計出雜訊的共變異數矩陣仍然是一個重要的課題。目前已經有許多估計雜訊分 佈的方法被提出來,包含空間的高通濾波器、頻率域的高通濾波器、正交子空間投影、主成份分析法和 費雪線性區別法(Fisher's Linear Discriminant Analysis,(Fisher's LDA))。這些方法在雜訊是高斯分佈時 都有很好的估計,但是當雜訊的分佈不是高斯分佈時,其效能不盡理想。這篇文章中我們採用無參數加 權特徵萃取法(Nonparametric Weighted Feature Extraction,(NWFE))來估計雜訊的分佈並和前人提出的方法 做比較。同時限制能量最小化法(Constrained Energy Minimization,(CEM))在遙測的目標物偵測上我們也加 上權重改善CEM 對目標光譜過於敏感的問題。

Abstract

Linear spectral mixture analysis (LSMA) has been widely used in remote sensing applications, and the Least Squares (LS) approach is one of the most effective methods for solving LSMA problem. Since the noise in LSMA from each band may not be independent and identical distributed (i.i.d.), it has been proven mathematically that the Noise Whitened Least Squares (NWLS) will outperform the original LS by making the noise i.i.d. with the noise whitening process. But how to estimate the noise covariance matrix is remain a challenge problem. Many methods have been proposed in the past including spatial high-pass filter, frequency domain high-pass filter, orthogonal subspace projection, principal component analysis and Fisher’s Linear Discriminant Analysis (Fisher’s LDA) based approach. They all perform well for Gaussian noise but encounter problems when the noise is ill distributed. In this study, we adopt Nonparametric Weighted Feature Extraction (NWFE) to estimate the noise distribution and compare the results. Furthermore, we also apply the weighted factor for Constrained Energy Minimization (CEM) to overcome its sensitivity problem to the target spectrum.

關鍵字

雜訊白化最小平方誤差法,無參數加權特徵萃取,限制能量最小化法

Keywords

Noise Whitened Least Squares (NWLS), Nonparametric Weighted Feature Extraction (NWFE), Constrained Energy Minimization (CEM)

附件檔名

華芸線上圖書館

N / A

備註說明

200712-12-4-335-341

Pages:

343-351

論文名稱

應用適應性濾波法於多頻譜影像之分類

Title

Adaptive Filtering Approaches to Multispectral Image Classification

作者

張麗娜,倪富荃

Author

Lena Chang,Fu-Chuan Ni

中文摘要

本研究針對多頻帶影像分類提出以影像特徵為基礎之適應性濾波法。首先考慮以線性濾波器的架構 進行影像分類,提出了適應性信號子空間投影法(Adaptive Signal Subspace Projection, ASSP),此法可於未知 背景訊號情況下偵測目標物。ASSP 使用適應性特徵分解演算法進行特徵值及特徵向量的遞迴式更新,藉 此,達到適應性影像分類之目的。接著,利用萃取的特徵資料作為倒傳遞類神經網路的輸入,以改善類 神經網路的收斂速度及影像分類的效能。論文中,我們提出以特徵值結合特徵向量之權重化特徵向量法, 可改善多頻譜影像目標物之偵測及分類之效能。 模擬結果顯示,適應性信號子空間投影法及以權重化特徵向量為輸入之類神經網路在影像分類上能 夠有效的減少雜訊效應,與傳統的韋恩濾波器法及以像素輸入法為基礎之倒傳遞網路相比,論文提出的 適應性濾波法具有較低的錯誤偵測率及快速的收斂速度。

Abstract

In the study, two adaptive classifiers based on image eigen-features are proposed for multispectral image classificationm. One is based on a liner filter with weights adaptively updated by the principal eigencompoments, and the other is an artificial neural network (ANN) with weights trained by the image eigen-features. We first propose an adaptive signal subspace projection (ASSP) approach to detect and extract target signatures in unknown background. The weights of ASSP are adjusted adaptively by using the eigen-features which are updated recursively by the adaptive eigen-decomposition algorithm. Then, we proposed an ANN classifier based on back propagation multilayer perception (BPMLP) with weights trained by the image eigen-features. Simulation results validate the image eigen-features can alleviate the noise effect in classification and the proposed ASSP and ANN classifiers have lower detection error and fast convergence rate than conventional Wiener filter and per-pixel ANN methods.

關鍵字

多頻帶影像,影像分類,適應性信號子空間投影法,埃根特徵,類神經網路

Keywords

multispectral image, image classification, adaptive signal subspace projection(ASSP), eigen-features, artificial neural network (ANN)

附件檔名

華芸線上圖書館

N / A

備註說明

200712-12-4-343-351

Pages:

353-364

論文名稱

以遺傳基因演算法為基礎的符號式迴歸引擎及其於全球定位系統之座標轉換上的應用

Title

A GP-Based Symbolic Regression Engine for the Transformation of GPS Coordinates

作者

周鴻儒,吳志宏

Author

Hung-Ju Chou, Chih-Hung Wu

中文摘要

全球定位系統之三維座標需要透過複雜的階層式數學計算才可轉換為二維座標。但是微小的誤差不 可避免的會在計算中被累積,使得精準度降低。在本論文中,我們提出一種新的符號式迴歸引擎來產生 GPS 座標轉換的迴歸方程式。迴歸方程式是透過樹狀結構所定義,再藉由遺傳基因演算法的交配、突變 與選擇來改變迴歸方程式的組合來尋找合適的方程式組合。為了增加迴歸引擎的效率,我們採用了可動 態改變機率的機制,加上樹狀修飾來降低公式複雜度,但是仍維持原公式的功能。若能夠得到計算複雜 度低的座標轉換公式,就能夠使得定位裝置在獨立電源的環境中,延長待機時間。此方法雖然不能夠降 低GPS 的系統誤差,但是透過定位資料成功地降低此GPS 的統計誤差。此研究的實驗資料採用TWD67 的大地座標系統,實驗結果顯示,我們確實能夠使用自行設計的符號式迴歸引擎來取得計算量低的GPS 座標轉換公式。

Abstract

Transformation of coordinates usually invokes level-wised processes wherein several sets of complicated equations are calculated. Unfortunately, the accuracy may be corrupted due to the accumulation of inevitable errors between the transformation processes. In this thesis, we present a new symbolic regression engine for generating regressive models for direct transformation from GPS signals to 2-D coordinates. The functional models to be found by the regression engine are represented in tree-based chromosome. Genetic operators like mutation, crossover, and reproduction are applied on such trees. In order to improve the efficiency of the regression process, we design some adaptive mechanisms which adjust the probabilities of applying genetic operations. Methods of trimming and pruning the regressive models for reducing their complexity are also design and implemented. Since target coordinates for a GPS application can be obtained by using simpler transformation formulas, the computational costs and inaccuracy can be reduced. The proposed method, though does not exclude systematic errors due to the imperfection on defining the reference ellipsoid and the reliability of GPS receivers, effectively reduces the statistical errors when the accurate Cartesian coordinates are known from the independent sources. From the experimental results where the target datum TWD67 is investigated, it seems that the proposed method can serve as a direct and feasible solution to the transformation of GPS coordinates.

關鍵字

遺傳基因演算法、符號式迴歸、全球定位衛星系統、座標轉換、TWD67

Keywords

GP, symbolic regression, transformation of GPS coordinates, TWD67

附件檔名

華芸線上圖書館

N / A

備註說明

200712-12-4-353-364

Pages:

365-379

論文名稱

由空載光達資料進行建物偵測與結構線萃取

Title

Building Detection and Structure Line Extraction from Airborne LiDAR Data

作者

王正楷,徐百輝

Author

Cheng-Kai Wang,Pai-Hui Hsu

中文摘要

本文提出一個由空載光達資料中進行建物偵測與特徵線萃取的方法,前者主要基於小波轉換與建物 的幾何特性,後者基於霍夫轉換與影像處理的方法。雖然光達資料富含豐富資訊,但其缺點為不易取得 屋頂之特徵,因此基於資料取向的建物重建方法,本研究即為獲取建物之特徵線以進行屋頂重建,其基 本原理為首先由原始的光達資料偵測出各個獨棟建物的位置,接著將特徵線分成外部輪廓線與內部結構 線並分別進行萃取,外部輪廓線主要利用霍夫轉換的技術得到,而內部結構線則利用共線分析來進行。 最後再將這兩部分的結構線進行屋頂模型的重建。由實驗成果顯示,具簡單、規則的屋頂類型如長方形、 山形屋與L 形屋頂皆可成功重建。

Abstract

An approach for building detection and feature lines extraction from airborne LiDAR data is proposed in this paper. The building detection is based on Wavelet Transform and geometric properties of buildings, and the extraction of feature lines is based on Hough Transform and image processing. Although LiDAR data contains rich surface information, the shortcoming is it cannot capture building features such as corners, edges, faces of roofs directly. For data-driven building reconstruction, the feature lines are essential to reconstruct the roof models. The basic idea of the proposed approach is to detect the location of each single building in the raw LiDAR data firstly. Then, the initial feature lines which are divided into external contour lines and internal structure lines are extracted respectively. The external contour lines are extracted using Hough Transform, and the internal structure lines are extracted using collinear analysis. Finally, the roof models are reconstructed by external contour lines as well as the internal structure lines of buildings. The experiment results showed that the regular and simple roofs such as rectangle roofs, gabled roofs and L-type roofs could be reconstructed successfully.

關鍵字

小波轉換,特徵線萃取,霍夫轉換,屋頂模型

Keywords

wavelet transform, feature line extraction, Hough Transform, roof model

附件檔名

華芸線上圖書館

N / A

備註說明

200712-12-4-365-379

Pages:

381-401

論文名稱

利用多尺度匹配自動套疊衛星雷達影像

Title

Automatic Registration of Satellite SAR Image Based on Multi-Resolution Matching

作者

洪浩倫,王志添,陳錕山

Author

Hao-Lun Hung, Chih-Tien Wang, Kun-Shan Chen

中文摘要

合成孔徑雷達具有全天候特性,可及時監測提供災害資訊,已經成為環境監測的重要工具。本文使 用不同時期、有相同地區重疊的重複軌道拍攝之雷達影像,利用重複軌道拍攝幾何關係相似特性,像元 攝像入射角度接近,在地表起伏地區,雷達影像幾何變形特徵一致,經過以多尺度匹配法為主的處理過 程,以及共軛點篩選,最後進行濾除斑駁雜訊的步驟,有效地在雷達影像上找到均勻分布且精確可靠的 共軛點,進行影像自動套疊,建置衛星雷達影像自動化套疊與變遷分析,以減少人為誤差及提昇效率。 本研究成果將可提升國土監測敏感度與滿足全天候山區崩塌監測實務需求。

Abstract

Due to its all-weather capability and stable repeat observations, synthetic aperture radar is able to provide timely information after a natural disaster. In this study, we developed a multi-scale matching technique to efficiently and effectively integrate multi-temporal for fast and accurate change detection. Experimental test results from RADARSAT and ALOS satellite radar images confirm that the proposed automatic registration scheme based on a multi-scale matching greatly reduces the artificial error and required computation, and thus is highly feasible for operational purpose.

關鍵字

合成孔徑雷達,自動套疊,多尺度匹配法

Keywords

Synthetic Aperture Radar, automatic registration, multi-scale matching

附件檔名

華芸線上圖書館

N / A

備註說明

200712-12-4-381-401

Pages:

403-417

論文名稱

以影像控制區塊解算航攝影像外方位參數實用策略

Title

Strategic Study on the Photo Orientation employing Control Patches

作者

陳詹閔,趙鍵哲

Author

Chan-Min Chen,Jen-Jer Jaw

中文摘要

利用既有圖資為控制資料完成待解算影像的定位工作為一實用的研究課題,藉此可免除或減少外業 測設控制點的工作量。除此之外,以自動化程序讀取控制實體資料庫中存放的相關圖資,除提昇蒐集效 率外,更減少資料整理時人力的浪費,而影像處理技術的引入,使控制資料在像片上的量測工作具備自 動化潛能。本研究利用影像控制區塊做為控制資料,搭配研究發展之匹配策略,以自動化方式量測控制 點,並解算影像外方位參數。基於實用性考量,本研究發展之操作系統具備人機檢核界面與變遷點回饋 機制,控制點量測模組則包含人工量測、半自動量測及全自動匹配供操作選擇,量測方式的彈性調變可 更貼近實務需求。由目前實際資料測試成果顯示,以全自動匹配模式進行解算之影像外方位參數在物空 間定點精度約化至像空間可達次像元(sub-pixel)等級之平面定位精度及1~2 個像元之高程定位精度,此研 究工作證實以影像控制區塊解算航攝影像外方位參數具備高效能及自動化之能力。

Abstract

Orienting the photogrammetric imagery by means of existing control entities is one of practical issues which aim to automatically acquire the control information from the database and perform the photo measurements in an attempt to reduce the labor involvement, as well as to promote the working efficiency towards orientation solutions. The author investigates in this study the strategic algorithms where the exterior orientations of the aerial photographic imagery are solved by matching with control patches. The proposed working scheme features itself with the designed platform of the human-machine interface where the measurements of control patches on the imagery can be achieved by through manual, semi-automatic, or fully automatic mode. Furthermore, the disagreements of control patches against the imagery, usually the phenomena of the scene change, are able to be identified and fed back to the system. The experiments show that the positioning quality of oriented imagery performed under the proposed scheme can reach up to sub-pixels and one to two pixels in horizontal and vertical components, respectively, a satisfaction towards orienting the imagery.

關鍵字

控制實體,影像控制區塊,匹配

Keywords

Control Entities, Control Patches, Matching

附件檔名

華芸線上圖書館

N / A

備註說明

200712-12-4-403-417

Pages:

419-429

論文名稱

多時影像與空載光達資料應用於地形變遷研究~以外傘頂沙洲為例

Title

Change Detection of Wai-Shan-Din Sandbar by Combining Multi-Temporal imageries and Airborne LiDAR data

作者

蕭國鑫, 劉進金, 陳大科,徐偉城,何心瑜

Author

Kuo-Hsin Hsiao, Jin-King Liu, Da-Ko Chen,Wei-Chen Hsu,Hou-Hsin Yu

中文摘要

本研究結合多時遙測衛星影像與三個時期的空載LiDAR 資料,分析外傘頂洲地區近35 年間的變化與 沙洲飄移趨勢,並比對與量化往內陸移動的速率。初步結果顯示,沙洲本體北段較為穩定,南段則呈逆 時鐘方向後退中;如1973~1986 年間,沙洲南段往東南方向飄移1.4 公里,北段沙洲亦向東方飄移近0.6 公里;1986~1990 年間,沙洲南端向東偏移420 公尺,北端為240 公尺;1992~1996 年間之沙洲北段較為穩 定,但南端約以每年162 公尺速率向陸地靠近;1997~1999 年間,沙洲最南端則往北移動了近150 公尺; 2000~2003 年間,沙洲南端約以每年50 公尺的速率往嘉義移動;2004~2005 年間平均移動速率增加為每年 65 公尺。另以空載光達資料分析2004~2006 年間之外傘頂洲地區的面積與體積變化,顯示0 公尺等高線 以上地區的面積與體積有減少趨勢;其中之面積由1813.10 公頃減少為1721.57 公頃,體積由17.56 百萬立 方公尺減少為16.24 百萬立方公尺。

Abstract

Multi-temporal satellite imageries and airborne LiDAR data are used in this study to understand the trend of change of Wai-Shan-Din Sandbar, and, thus to estimate the moving rate of the sandbar toward the inner land in recent 35 years. Results are as follows: (1) Images between 1973 to 1990 shows that the sandbar is retreating from the sea toward the land to the east side in a counter-clockwise movement with a larger amount in the southern part of 1.82 kilometers and smaller amount in the northern part of 0.84 kilometers. (2) From 1992 to 1996, the northern part of the sandbar was stable but the southern part was moving counter-clockwise with a rate of 162m per year. (3) From 1997 to 1999, the southern part of the sandbar shifting 150 meters northward. From 2000 to 2003, the annual rate is 50 meters toward the land to the east. (4) Three times of DEMs from 2004 to 2006 were obtained by airborne LiDAR. The northern part of the sandbar was subject very subtle change according to the overlay of thematic maps of zero-meter lines abstracted from Lidar DEMs. However, the southern part shows a change of around 110 to 130 meters toward the land to the east. (5) The zero-meter thematic maps and the volumes within zero-meter lines also show that the area of the sandbar decreased from 1813 to 1721 hectares, and the volume changed from 17.56 to 16.24 million m ³. It is concluded that satellite imageries give a long time of records for understanding the trend of the 2D coastal lines. However, LiDAR enhances a possibility of understanding the change patterns in 3D, including the volume of change.

關鍵字

遙測,變遷偵測,空載光達

Keywords

Remote Sensing, Change Detection, Airborne LiDAR

附件檔名

華芸線上圖書館

N / A

備註說明

200712-12-4-419-429

Pages:

431-445

論文名稱

改良式自動種子區塊成長於航測影像分割之研究

Title

A Study on Segmentation of Remotely Sensed Forest Images by Using The Improved Seeded Region Growing Algorithm

作者

吳俊霖, 曾振益

Author

Jiunn-Lin Wu,Jen-Yi Tzeng

中文摘要

影像分割(image segmentation)在影像處理上是一個重要的議題,尤其在遙測或航測影像上常常可以看 到利用影像分割為地物識別的前處理步驟,所以分割的好壞與否往往佔有巨大的影響性。目前分割的方 法雖然有許多種,但是要達到令人滿意的結果並不是件簡單的事情。本論文提出一改良式的自動種子區 塊成長演算法(seeded region growing, SRG)來達成對彩色森林航測影像分割的目的,其中加入離散餘弦轉換 (discrete cosine transform, DCT)為紋理特徵,之後依序進行種子的自動產生以及讓其成長到充滿整張影像 圖,最後進行區塊合併(region-merging)來改善品質。實驗結果顯示所提方法在森林航測影像上能有不錯的 分割結果,速度最多可以比JSEG 演算法提升一倍。

Abstract

Image segmentation is an important topic in many applications of image processing. It is a procedure that divides different regions or objects of the image, and thus we can retrieve the regions of interest. The images of the different tree species usually have the similar color distribution, but the differences between them are only texture information. In this paper, an efficient segmentation method based on seeded region growing is proposed for the color remote sensing images of forest, it performs the unsupervised segmentation. We use the coefficients of discrete cosine transform as the texture features, the seeds are then produced automatically by considering both of the color features and texture features. The seeds grow to their boundaries until all pixels are classified. Finally, a region-merging process is adopted to improve the segmentation result. Experimental results show that the proposed method can separate successfully the different color texture in the remote sensing images of forest, and the performance is better than the JSEG algorithm.

關鍵字

影像分割,區塊成長,紋理特徵,離散離弦轉換,JSEG

Keywords

Image segmentation, Region growing; Texture feature; Discrete cosine

附件檔名

華芸線上圖書館

N / A

備註說明

200712-12-4-431-445

Pages:

447-456

論文名稱

以SPOT 影像及數值地形模型推估集水區泥砂產量

Title

Prediction of Sediment Yield Using SPOT Imagery and Digital Terrain Model

作者

江陽聖, 陳錕山, 梁隆鑫, 王志添

Author

Yang-Sheng Chiang, Kun-Shan Chen, Long-Shin Liang,Chih-Tien Wang

中文摘要

本研究應用光學SPOT 衛星影像進行2001-2006 年石門水庫、頭前溪、大甲溪、高屏溪上源集水區裸 露崩塌地判釋及泥砂沖蝕量推估,研究首先藉由實驗樣區植生分析,並應用數值地形模型探討崩塌發生 的區位特徵,制定出崩塌判釋標準流程,分析並探討歷年崩塌變遷狀況,並藉由現地調查及航照判釋資 料進行判釋成果的比對驗證,研究顯示2006 年石門水庫、頭前溪、大甲溪、高屏溪上源集水區裸露崩塌 地面積分別為634 ha、236 ha、1189 ha、4308 ha。在集水區產砂推估上,首先制定泥砂沖刷演算流程, 區分點源及非點源式的產砂來源,其中非點源式的表土沖刷以通用土壤流失公式進行推估,點源式的產 砂來源則以判釋崩塌區及崩塌深度進行分析,再藉由泥砂遞移概念演算進入庫區或集水區出流點的砂石 總量,並分析歷年變化狀況。經由分析演算,歷年表土沖刷變化與年降雨量呈現相關,而在空間分布上, 高表土流失區域與裸露崩塌區位相符合,2006 年以上各集水產砂量分別為1,070,097 m3、323,540 m3、 1,836,431 m3、4,824,430 m3。經與石門水庫歷年實測清淤量及淤砂量的比對分析,此泥砂沖刷演算值與 產砂變遷趨勢一致。

Abstract

Heavy rainfall often triggers widespread soil erosion and landslide hazard in mountainous terrain, resulting in sediment deposition and loss of reservoir capacity. This research aims to identify major sediment sources and predict watershed yield by using satellite images and GIS techniques. Optical satellite images, specifically those of SPOT series, were used to identify landslide areas from 2001 to 2006. To distinguish landslides from high vegetated areas, field studies were conducted for investigation of normalized difference vegetation index (NDVI) covering several major land covers to determine the threshold value for bare land. Slope features, based on spatial analysis of Digital Terrain Model, were also introduced to differentiate landslide from other low vegetated area. Study showed that landslide covered about 634 hectares at Shihmen Reservoir, 236 hectares at Touchien catchment, 1,189 hectares at Dajia catchment , and 4,308 hectares at Kaoping catchment in post-typhoon season images of 2006. To estimate soil erosion and the mechanism of sediment transport, the Universal Soil Loss Equation (USLE) and soil delivery ratio were used to estimate non-point sources of soil erosion, and those of point sources were determined by the identified landslide areas, which were then multiplied by the predicted depth of weathered layer to obtain the total volume. Study indicated that the sediment yield of Shihmen Reservoir, Touchien Creek, Dajia creek, and Kaoping Creek were estimated as 1,070,097 m3, 323,540 m3, 1,836,431 m3, 4,824,430 m3, respectively. Finally, under the assistance of Northern Region Water Resources Office, our predicted results were validated by the measured sediment yield of Shihmen Reservoir.

關鍵字

崩塌地,產砂量,數值地形模型,通用土壤流失公式,SPOT 衛星

Keywords

Landslide, Sediment Yield, Digital Terrain Model, SPOT Image, Universal Soil Loss Equation

附件檔名

華芸線上圖書館

N / A

備註說明

200712-12-4-447-456

Pages:

457-478

論文名稱

使用CSR 演算法重建屋頂面模型

Title

Building Roof Reconstruction by Using CSR Approach

作者

趙鍵哲,鄭傑中

Author

Jen-Jer Jaw, Chieh-Chung Cheng

中文摘要

本文設計一套利用三維結構線重建屋頂面模型之幾何推論演算法,目標除了探討從不同資料來源所 提供的三維結構線中建立初始屋頂面模型的可行性外,也融合三維結構線與航攝影像直線特徵以提升屋 頂面模型的品質。演算法分為建構-成型-改良(Construct-Shape-Refine, CSR)三個幾何推論(Geometric Inference) 之程序。首先建構為建立屬於同一個屋頂面之三維結構線間的位相關係。而成型則將每個屋頂面上之可 視三維結構線進行平差計算以獲得三維屋角點坐標與理論精度,並考量相鄰較低樓層的邊緣線易受遮蔽 影響,利用最短路徑(Shortest Path)的概念以相鄰之高度較高的建物邊緣線補償受遮蔽的邊緣線,並建立屋 頂面間之空間位相關係以及組成此一階段之屋頂面模型物件。在改良階段則考慮若能在相同的實驗區內 獲得其它圖資(如:航空影像、地形圖與光達資料),此時可進行資料融合以提升屋頂面模型的品質。實驗 結果顯示,建構-成型兩步驟能從不同資料來源所得到的三維結構線中重建初始屋頂面模型。而在改良的 階段中,除了可處理同為三維結構線圖資之融合作業以提升屋頂面模型幾何品質外,特別是當融合三維 結構線與航攝影像圖資時,使用三維結構線確實有助於影像中建物邊緣線之辨識,而利用平差程序處理 三維結構線與航測經由前方交會所得到的三維屋頂面邊緣線,能獲致平面與高程精度增益的融合成果。

Abstract

3D structure lines are geometric evidences of building roofs and can be resulted from photogrammetric mapping process, feature extraction of LiDAR data sets or other sources. Hence, 3D structure lines by nature are advantageous for inferring to building roof reconstruction. The objective of this investigation is to present a novel algorithm of building roof reconstruction, termed CSR (Construct-Shape-Refine) in this study. The proposed algorithm aims at reconstructing building roof model purely by employing 3D structure lines or integrating 3D structure lines and imagery line features. Geometric inferences are imposed at the stage of Construct where topological relationship of the 3D structure lines is established while 3D coordinates of roof corners are adjusted and estimated through Shape processes, apart from compensating the hidden boundaries, if any. The efficiencies of two streams, fusion of 3D structure lines that result from different sources or fusing 3D structure lines with photogrammetric line features, are gained as promoting the building roof quality via Refine workflow. The experiments of the Construct-Shape steps demonstrate that the proposed method is independent of building roof type as well as whether 3D structure lines are complete for both successful and efficient performance of building roof reconstruction on 3D line basis. Furthermore, the Refine step offered more robust and satisfactory building reconstruction result as compared to the situation when only single data set was attempted.

關鍵字

位相關係,幾何推論,融合,屋頂面重建

Keywords

Topological Relationship; Geometric Inference; Fusion; Building Roof Reconstruction.

附件檔名

華芸線上圖書館

N / A

備註說明

200712-12-4-457-478

Pages:

479-488

論文名稱

以光譜混合分析模式推估SPOT 衛星影像之森林豐富度

Title

Estimation of forest abundance by spectral mixture analysis on SPOT imagery

作者

呂明倫,鍾玉龍

Author

Ming-Lun Lu,Yuh-Lurng Chung

中文摘要

光譜混合分析模式(spectral mixture analysis, SMA)係衛星影像分類中,降低混合像元問題之主要方法, 本研究之目的即應用SMA 推估SPOT 衛星影像中墾丁國家公園之森林豐富度。以線性光譜混合模式解算, 可獲取綠植生(green vegetation, GV)與裸地兩種分量影像,其中GV 以及一般常見的常態化差異植生指標 (normalized difference vegetation index, NDVI)皆適於推估森林豐富度之指標。為評估兩者之精確度,本研究 採用1×1 m 之高解析力IKONOS 影像,用以量測實際之森林豐富度,並計算平均絕對值百分比、均方根 誤差與Theil's U 不等係數等3 種評估指標。研究結果發現,3 種評估指標中,GV 之精確度均優於NDVI, 因此未來對於森林監測的工作上,SMA 應為潛力較佳之方法。

Abstract

Spectral mixture analysis (SMA) approach is one of the most popular methods for reducing the mixed pixel problem on satellite image classification. The objective of this study was to examine the applicability of SMA to the estimation of forest abundance using SPOT image in the Kenting National Park. We acquired three fraction images which were green vegetation (GV) and soil derived from linear spectral mixture model. In general, both the GV and normalized difference vegetation index (NDVI) were to examine the forest abundance, and for the purpose to compare the examine accuracy, the forest abundance from high resolution (1×1 m) IKONOS image was derived. Accuracy assessment of the GV and NDVI was to calculate three indices, which were mean absolute percentage, root mean square and Theil’s U inequality coefficient. The results showed that the GV was higher accuracy than NDVI on the three indices, meaning that the SMA could be an efficient tool for monitoring forest.

關鍵字

混合像元、線性光譜混合模式,分量影像,森林豐富度

Keywords

mixed pixel, linear spectral mixture model, fraction images, forest abundance

附件檔名

華芸線上圖書館

N / A

備註說明

200712-12-4-479-488

Pages:

489-507

論文名稱

以浮測模型理論萃取三維空間資訊-以建物重建為例

Title

Theory of Floating Model in 3D Spatial Information Extraction – A Case Study on Building Reconstruction

作者

王聖鐸,曾義星

Author

Sendo Wang,Yi-Hsing Tseng

中文摘要

數十年來攝影測量一直被認為是最有效且精確的測繪技術,然而傳統以浮測標逐點量測的方式重建 三維建物模型時,操作員需要專注於屋角點的量測及點位之連結,是萃取三維空間資訊的瓶頸。本研究 採用模型式建物萃取法(Model-based Building Extraction, MBBE),將傳統的浮測標擴充為浮測模型(Floating Model),使量測的單元不再是抽象的一個點位,而是許多種可伸縮、旋轉、移動的三維模型。零維的浮 測標拓展到三維的浮測模型,除了具備可調整的三維位置參數外,還依模型種類增加了各方向的伸縮尺 度、空間旋轉等參數,可想像成一個漂浮在空間中,可移動、旋轉、縮放大小以量測地物的模型。將浮 測模型投影至所有影像,並套合至影像上的目標地物,便有如回復攝影瞬間之幾何空間條件,此時之模 型參數即為最佳解,此即以浮測模型萃取三維空間資訊之基本理論。本研究建置了點、線、面、立體四 大類基本元件模型庫,量測員可以依需要選擇適當元件模型,在多張重疊像片上進行模型式的量度。並 可依模型精細程度需求,以數個基本元件模型分部萃取,再透過布林運算規則組合為複合模型,因此能 適用於萃取大多數的三維建物。本研究並提出一套半自動化萃取策略,操作員透過人機互動介面將模型 套合至所有影像,交由電腦透過最小二乘模型-影像套合演算法自動計算最佳套合。以便在已知相片方位 的條件下萃取地物的三維空間資訊,或在已知地物模型的條件下利用模型求解相片的外方位元素。透過 實驗案例證明,浮測模型理論確可有效地萃取建物三維空間資訊,提高三維塑模之效率,並能達到傳統 攝影測量之精度要求。

Abstract

Photogrammetry has been considered as the most efficient technique for extracting 3D spatial information in the last few decades. However, the point-by-point measurement of using floating mark has become the bottleneck while reconstructing the 3D city model. In this paper, we expanded the floating mark to the floating model based on the concept of model-based building extraction. The measuring tool is no longer an abstract point but many kinds of 3D model, which can be scaled, rotated, or moved in the space. The floating model is defined with a datum point indicates the model’s position. Each kind of models is associated with a set of pose parameters to describe its rotation about the three orthogonal axes and shape parameters to describe its scales along predefined directions. In other words, the floating model is a flexible entity floating in the space, and can be adjusted to fit the object by these parameters. If the model parameters are good enough to represent the 3D spatial information of the object, the projection of the floating model on every overlapped image will all be coincident to the object’s outlines. In order to meet the needs of building reconstruction, we designed several primitive models that can be categorized into four kinds: point, line segment, surface, and solid. By means of human-computer interface, the operator is able to choose the most suitable model and measure the object on multiple images. The complicated building can be split into several parts, modeled part-by-part, and finally joined into one complex model. Based on the floating model theory and model-based building extraction, we proposed a semi-automated strategy. A friendly human-machine interface is designed for the operator to choose and adjust the floating model to fit the images manually. Then, the computer calculate the optimal fit by an ad hoc Least-Squares Model-Image Fitting algorithm. Thus the 3D spatial information can be extracted object-by-object, which increases the efficiency and accuracy.

關鍵字

浮測模型,三維建物模型,模型式建物萃取,數值攝影測量

Keywords

Floating Model, 3D Building Model, Model-based Building Extraction, Digital Photogrammetry

附件檔名

華芸線上圖書館

N / A

備註說明

200712-12-4-489-507

Pages:

509-526

論文名稱

多分類器融合權重分配法之研究

Title

A New Weighting Scheme with Multiple Classifiers Fusion for Image Classification

作者

曾裕強,陳錕山

Author

Y. C. Tzeng, K. S. Chen

中文摘要

資料融合的關鍵技術之一乃如何有效萃取來自不同感測器的互補資訊。本文即探討利用多分類器系 統來達到這個目的。多分類器系統中的必要手段為不同資料來源的權重分配;本文分別提出三種方案: 變異減低法、均方根距離法與平均距離法。實例中我們利用SAR 影像與光學影像融合於地物分類作為分 析評估上述權重分配的性能。結果顯示整體分類精度有大幅度的提升,而三種方案中均方根距離法與平 均距離法皆優於變異減低法。

Abstract

One of the key prospects of data fusion is focused on exploiting the complementary information among different sensors. In this paper, the multiple classifiers approach is utilized for the multisource classification/data fusion to fully utilize as much of the available information among different data sources as possible. Three different weighting policies (variance reduction technique, rms distance weighting, and average distance weighting) applied to the multiple classifiers approach are introduced. The performance of each combination method was demonstrated and compared with the fusion of the SAR and optical images for the terrain cover classification. Experimental results show that the classification accuracy is dramatically improved by making use of the proposed method. In addition, both the multiple classifiers using the rms (root mean squared) distance weighting and the average distance weighting outperform that of using the variance reduction technique.

關鍵字

影像融合,SAR,地物分類,多分類器

Keywords

Image fusion, SAR, terrain classification, Multiple Classifiers

附件檔名

華芸線上圖書館

N / A

備註說明

200712-12-4-509-526

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