Much research effort has been devoted to producing algorithms that contribute directly or indirectly to the extraction of 3D information from a wide variety of types of scenes and conditions of image capture. The research work presented in this thesis is aimed at three distinct applications in this area: interactively extracting 3D points from a pair of uncalibrated images in a flexible way; finding corresponding points automatically in high resolution images, particularly those of archaeological scenes captured from a freely moving light aircraft; and improving a correlation approach to dense disparity mapping leading to 3D surface reconstructions. The fundamental concepts required to describe the principles of stereo vision, the camera models, and the epipolar geometry described by the fundamental matrix are introduced, followed by a detailed literature review of existing methods. An interactive system for viewing a scene via a monochrome or colour anaglyph is presented which allows the user to choose the level of compromise between amount of colour and ghosting perceived by controlling colour saturation, and to choose the depth plane of interest. An improved method of extracting 3D coordinates from disparity values when there is significant error is presented. Interactive methods, while very flexible, require significant effort from the user finding and fusing corresponding points and the thesis continues by presenting several variants of existing scale invariant feature transform methods to automatically find correspondences in uncalibrated high resolution aerial images with improved speed and memory requirements. In addition, a contribution to estimating lens distortion correction by a Levenberg Marquard based method is presented; generating data strings for straight lines which are essential input for estimating lens distortion correction. The remainder of the thesis presents correlation based methods for generating dense disparity maps based on single and multiple image rectifications using sets of automatically found correspondences and demonstrates improvements obtained using the latter method. Some example views of point clouds for 3D surfaces produced from pairs of uncalibrated images using the methods presented in the thesis are included. / Al-Baath University / The appendices files and images are not available online.

A construção automática de grandes mosaicos a partir de imagens digitais de alta resolução é uma área de grande importância, encontrando aplicações em diferentes áreas, como agricultura, meteorologia, sensoriamento remoto e biológicas. Na agricultura, a eficiência no processo de tomada de decisão para controle de pragas, doenças ou queimadas está relacionada com a obtenção rápida de informações. Até o presente momento este controle vem sendo feito de maneira semiautomática, necessitando obter o modelo digital do terreno, fazer a ortorretificação de imagens, inserir marcações manualmente no solo, para que um software possa construir um mosaico de maneira convencional. Para automatizar este processo, o presente projeto propõe três metodologias (1, 2, 3) baseadas em algoritmos já consolidados na literatura (SIFT, BBF e RANSAC) e processamento paralelo (OpenMP), utilizando imagens aéreas agrícolas de alta resolução, de pastagens e plantações de diversas culturas. As metodologias diferem na maneira como os cálculos são realizados para a construção dos mosaicos. Construir mosaicos com este padrão de imagem não é uma tarefa trivial, pois requer alto esforço computacional para processamento destas imagens. As metodologias incluem um pré-processamento das imagens para minimizar possíveis distorções que surgem no processo de aquisição de imagens e contém também algoritmos para suavização das emendas das imagens no mosaico. A base de imagens, denominada base de imagens sem redimensionamento, foi construída a partir de imagens com dimensão de 2336 x 3504 pixels (100 imagens divididas em 10 grupos de 10 imagens), obtidas na região de Santa Rita do Sapucaí - MG, as quais foram utilizadas para validar a metodologia. Outra base de imagens, referida como base de imagens redimensionada, contêm 200 imagens de 533 x 800 pixels (10 grupos de 20 imagens) e foi utilizada para avaliação de distorção para comparação com os softwares livres Autostitch e PTGui, os quais possuem parâmetros pré-definidos para a resolução de 533 x 800 pixels. Os resultados do tempo de processamento sequencial para as três metodologias evidenciaram a metodologia 3 com o menor tempo, sendo esta 63,5% mais rápida que a metodologia 1 e 44,5% do que a metodologia 2. O processamento paralelo foi avaliado para um computador com 2, 4 e 8 threads (4 núcleos físicos e 4 núcleos virtuais), reduzindo em 60% o tempo para a construção dos mosaicos de imagens para a metodologia 1. Verificou-se que um computador com 4 threads (núcleos físicos) é o mais adequado em tempo de execução e Speedup, uma vez que quando se utilizam 8 threads são incluídos as threads virtuais. Os resultados dos testes de distorção obtidos evidenciam que os mosaicos gerados com a metodologia 1 apresentam menores distorções para 7 grupos de imagens em um total de 10. Foram também avaliadas as distorções nas junções de cinco mosaicos constituídos apenas por pares de imagens utilizando a metodologia 3, evidenciando que a metodologia 3 apresenta menor distorção para 4 mosaicos, em um total de 5. O presente trabalho contribui com a metodologia 2 e 3, com a minimização das distorções das junções do mosaico, com o paralelismo em OpenMP e com a avaliação de paralelismo com MPI. / The automatic construction of large mosaics from high resolution digital images is an area of great importance, which finds applications in different areas, especially agriculture, meteorology, biology and remote sensing. In agriculture, the efficiency of decision making is linked to obtaining faster and more accurate information, especially in the control of pests, diseases or fire control. So far this has been done semiautomatically and it is necessary to obtain the digital terrain model, do the orthorectification of images, insert markings on the ground by manual labor, so that software can build a mosaic in the conventional way. To automate this process, this project proposes three methodologies (1, 2, 3) based on algorithms already well-established in the literature (SIFT, BBF e RANSAC) and parallel processing (OpenMP), using high resolution/size aerial images agricultural of pasture and diverse cultures. The methodologies differ in how the calculations are performed for the construction of mosaics. Build mosaics with this kind of picture isn´t a trivial task, as it requires high computational effort for processing these images. The methodologies include a pre-processing of images to minimize possible distortions that arise in the process of image acquisition and also contain algorithms for smoothing the seams of the images in the mosaic. The image database, called image database without scaling, was constructed from images with dimensions of 2336 x 3504 pixels (100 images divided into 10 groups of 10 pictures), obtained in the region of Santa Rita do Sapucaí - MG, which were used to validate the methodology. Another image database, referred to as base images resize, contains 200 images of 533 x 800 pixels (10 groups of 20 pictures). It was used for evaluation of distortion compared to the free softwares Autostitch and PTGui, which have pre-defined parameters for the resolution of 533 x 800 pixels. The results of sequential processing time for the three methodologies showed the methodology 3 with the shortest time, which is 63.5% faster than the methodology 1 and 44.5% faster than the methodology 2. Parallel processing was evaluated for a computer with 2, 4 and 8 threads (4 physical cores and 4 virtual cores), reducing by 60% the time to build the mosaics of images for the methodology 1. It was found that a computer with 4 threads (physical cores) is most appropriate in execution time and Speedup, since when using 8 threads, threads virtual are included. The test results of distortion show that the mosaics generated with the methodology 1 have lower distortion for 7 groups of images in a total of 10. Distortions at the junctions of five mosaics consisting only of pairs of images were also evaluate utilizing the methodology 3, indicating that the methodology 3 has less distortion for 4 mosaics, for a total of 5. Contributions of this work have been the methodologies 2 and 3, with the distortions minimization of the mosaic junction, the parallelism in OpenMP and the assessment of parallelism with MPI.

A construção automática de grandes mosaicos a partir de imagens digitais de alta resolução é uma área de grande importância, encontrando aplicações em diferentes áreas, como agricultura, meteorologia, sensoriamento remoto e biológicas. Na agricultura, a eficiência no processo de tomada de decisão para controle de pragas, doenças ou queimadas está relacionada com a obtenção rápida de informações. Até o presente momento este controle vem sendo feito de maneira semiautomática, necessitando obter o modelo digital do terreno, fazer a ortorretificação de imagens, inserir marcações manualmente no solo, para que um software possa construir um mosaico de maneira convencional. Para automatizar este processo, o presente projeto propõe três metodologias (1, 2, 3) baseadas em algoritmos já consolidados na literatura (SIFT, BBF e RANSAC) e processamento paralelo (OpenMP), utilizando imagens aéreas agrícolas de alta resolução, de pastagens e plantações de diversas culturas. As metodologias diferem na maneira como os cálculos são realizados para a construção dos mosaicos. Construir mosaicos com este padrão de imagem não é uma tarefa trivial, pois requer alto esforço computacional para processamento destas imagens. As metodologias incluem um pré-processamento das imagens para minimizar possíveis distorções que surgem no processo de aquisição de imagens e contém também algoritmos para suavização das emendas das imagens no mosaico. A base de imagens, denominada base de imagens sem redimensionamento, foi construída a partir de imagens com dimensão de 2336 x 3504 pixels (100 imagens divididas em 10 grupos de 10 imagens), obtidas na região de Santa Rita do Sapucaí - MG, as quais foram utilizadas para validar a metodologia. Outra base de imagens, referida como base de imagens redimensionada, contêm 200 imagens de 533 x 800 pixels (10 grupos de 20 imagens) e foi utilizada para avaliação de distorção para comparação com os softwares livres Autostitch e PTGui, os quais possuem parâmetros pré-definidos para a resolução de 533 x 800 pixels. Os resultados do tempo de processamento sequencial para as três metodologias evidenciaram a metodologia 3 com o menor tempo, sendo esta 63,5% mais rápida que a metodologia 1 e 44,5% do que a metodologia 2. O processamento paralelo foi avaliado para um computador com 2, 4 e 8 threads (4 núcleos físicos e 4 núcleos virtuais), reduzindo em 60% o tempo para a construção dos mosaicos de imagens para a metodologia 1. Verificou-se que um computador com 4 threads (núcleos físicos) é o mais adequado em tempo de execução e Speedup, uma vez que quando se utilizam 8 threads são incluídos as threads virtuais. Os resultados dos testes de distorção obtidos evidenciam que os mosaicos gerados com a metodologia 1 apresentam menores distorções para 7 grupos de imagens em um total de 10. Foram também avaliadas as distorções nas junções de cinco mosaicos constituídos apenas por pares de imagens utilizando a metodologia 3, evidenciando que a metodologia 3 apresenta menor distorção para 4 mosaicos, em um total de 5. O presente trabalho contribui com a metodologia 2 e 3, com a minimização das distorções das junções do mosaico, com o paralelismo em OpenMP e com a avaliação de paralelismo com MPI. / The automatic construction of large mosaics from high resolution digital images is an area of great importance, which finds applications in different areas, especially agriculture, meteorology, biology and remote sensing. In agriculture, the efficiency of decision making is linked to obtaining faster and more accurate information, especially in the control of pests, diseases or fire control. So far this has been done semiautomatically and it is necessary to obtain the digital terrain model, do the orthorectification of images, insert markings on the ground by manual labor, so that software can build a mosaic in the conventional way. To automate this process, this project proposes three methodologies (1, 2, 3) based on algorithms already well-established in the literature (SIFT, BBF e RANSAC) and parallel processing (OpenMP), using high resolution/size aerial images agricultural of pasture and diverse cultures. The methodologies differ in how the calculations are performed for the construction of mosaics. Build mosaics with this kind of picture isn´t a trivial task, as it requires high computational effort for processing these images. The methodologies include a pre-processing of images to minimize possible distortions that arise in the process of image acquisition and also contain algorithms for smoothing the seams of the images in the mosaic. The image database, called image database without scaling, was constructed from images with dimensions of 2336 x 3504 pixels (100 images divided into 10 groups of 10 pictures), obtained in the region of Santa Rita do Sapucaí - MG, which were used to validate the methodology. Another image database, referred to as base images resize, contains 200 images of 533 x 800 pixels (10 groups of 20 pictures). It was used for evaluation of distortion compared to the free softwares Autostitch and PTGui, which have pre-defined parameters for the resolution of 533 x 800 pixels. The results of sequential processing time for the three methodologies showed the methodology 3 with the shortest time, which is 63.5% faster than the methodology 1 and 44.5% faster than the methodology 2. Parallel processing was evaluated for a computer with 2, 4 and 8 threads (4 physical cores and 4 virtual cores), reducing by 60% the time to build the mosaics of images for the methodology 1. It was found that a computer with 4 threads (physical cores) is most appropriate in execution time and Speedup, since when using 8 threads, threads virtual are included. The test results of distortion show that the mosaics generated with the methodology 1 have lower distortion for 7 groups of images in a total of 10. Distortions at the junctions of five mosaics consisting only of pairs of images were also evaluate utilizing the methodology 3, indicating that the methodology 3 has less distortion for 4 mosaics, for a total of 5. Contributions of this work have been the methodologies 2 and 3, with the distortions minimization of the mosaic junction, the parallelism in OpenMP and the assessment of parallelism with MPI.

Atualmente, as atividades do agronegócio necessitam, como todas as demais áreas, de soluções inovadoras que potencializem as mais diferentes demandas do negócio; a agricultura de precisão é um caminho que vem se mostrando eficiente na tomada de decisão. Nos dias atuais, a aplicação do veículo aéreo não tripulado- VANT ou também conhecido como aeronave remotamente pilotada- ARP vem se mostrando uma crescente ferramenta de inserção dentro deste contexto e aplicação. A tomada de decisão do agricultor, seja ele de pequeno, médio ou grande porte, pode ser auxiliada com o uso de equipamentos e softwares que vêm se tornando uma prática usual tanto nas atividades da agricultura como em outras tantas, isso devido a sua fácil aplicação, baixo custo e grande possibilidade de aplicações nas diferentes atividades do agronegócio. Os veículos de asas rotativas são, nesse contexto de uso, atrelados a aplicativos específicos, uma solução eficaz na gestão de diferentes culturas e atividades no agronegócio. Os resultados observados com os voos realizados, com as coletas de imagens, bem como o mapeamento de culturas e propriedades rurais se mostraram satisfatórios ao longo da pesquisa, tanto na forma de controle de voo manual quanto no modo autônomo de coleta de dados. Outro fator que possibilitou a pesquisa foi o uso de aplicativos de imagem e rota de voo, possibilitando cumprir os diferentes objetivos propostos na pesquisa. / Currently, the agribusiness activities require, as all other areas, innovative solutions that empower the most different demands of business; the precision agriculture is a path that has been showing efficient decision-making. Nowadays, the application of unmanned aerial vehicle UAV - or also known as aircraft remotely piloted - ARP has been showing a growing insertion tool within this context and application. The farmer\'s decision making, be he small, medium or large, can be aided with the use of equipment and software that has become an usual practice both in the activities of agriculture as in others, that due to its easy application, low cost and great possibility of applications in the different activities of the agribusiness. Rotary wing vehicles are, in this context of use, tied to specific applications, an effective solution in different management cultures and activities in agribusiness. The results observed with the flights taken, with collections of images, as well as the mapping of cultures and rural properties have proven satisfactory throughout the research, both in the form of manual flight control mode of collection of data, another factor that enabled the research was the use of imaging applications and flight path, in this way, it was possible to accomplish the different objectives proposed in the research.

Atualmente, as atividades do agronegócio necessitam, como todas as demais áreas, de soluções inovadoras que potencializem as mais diferentes demandas do negócio; a agricultura de precisão é um caminho que vem se mostrando eficiente na tomada de decisão. Nos dias atuais, a aplicação do veículo aéreo não tripulado- VANT ou também conhecido como aeronave remotamente pilotada- ARP vem se mostrando uma crescente ferramenta de inserção dentro deste contexto e aplicação. A tomada de decisão do agricultor, seja ele de pequeno, médio ou grande porte, pode ser auxiliada com o uso de equipamentos e softwares que vêm se tornando uma prática usual tanto nas atividades da agricultura como em outras tantas, isso devido a sua fácil aplicação, baixo custo e grande possibilidade de aplicações nas diferentes atividades do agronegócio. Os veículos de asas rotativas são, nesse contexto de uso, atrelados a aplicativos específicos, uma solução eficaz na gestão de diferentes culturas e atividades no agronegócio. Os resultados observados com os voos realizados, com as coletas de imagens, bem como o mapeamento de culturas e propriedades rurais se mostraram satisfatórios ao longo da pesquisa, tanto na forma de controle de voo manual quanto no modo autônomo de coleta de dados. Outro fator que possibilitou a pesquisa foi o uso de aplicativos de imagem e rota de voo, possibilitando cumprir os diferentes objetivos propostos na pesquisa. / Currently, the agribusiness activities require, as all other areas, innovative solutions that empower the most different demands of business; the precision agriculture is a path that has been showing efficient decision-making. Nowadays, the application of unmanned aerial vehicle UAV - or also known as aircraft remotely piloted - ARP has been showing a growing insertion tool within this context and application. The farmer\'s decision making, be he small, medium or large, can be aided with the use of equipment and software that has become an usual practice both in the activities of agriculture as in others, that due to its easy application, low cost and great possibility of applications in the different activities of the agribusiness. Rotary wing vehicles are, in this context of use, tied to specific applications, an effective solution in different management cultures and activities in agribusiness. The results observed with the flights taken, with collections of images, as well as the mapping of cultures and rural properties have proven satisfactory throughout the research, both in the form of manual flight control mode of collection of data, another factor that enabled the research was the use of imaging applications and flight path, in this way, it was possible to accomplish the different objectives proposed in the research.

The Swedish armed forces use the Single Source Intelligent Cell (SSIC), developed by Saab, for analysis of aerial reconnaissance video and report generation. The analysis can be time-consuming and demanding for a human operator. In the analysis workflow, identifying vehicles is an important part of the work. Artificial Intelligence is widely used for analysis in many industries to aid or replace a human worker. In this paper, the possibility to aid the human operator with air reconnaissance data analysis is investigated, specifically, object detection for finding cars in aerial images. Many state-of-the-art object detection models for vehicle detection in aerial images are based on a Convolutional Neural Network (CNN) architecture. The Faster R-CNN- and SSD-based models are both based on this architecture and are implemented. Comprehensive experiments are conducted using the models on two different datasets, the open Video Verification of Identity (VIVID) dataset and a confidential dataset provided by Saab. The datasets are similar, both consisting of aerial images with vehicles. The initial experiments are conducted to find suitable configurations for the proposed models. Finally, an experiment is conducted to compare the performance of a human operator and a machine. The results from this work prove that object detection can be used to supporting the work of air reconnaissance image analysis regarding inference time. The current performance of the object detectors makes applications, where speed is more important than accuracy, most suitable.

Made available in DSpace on 2014-12-17T15:47:49Z (GMT). No. of bitstreams: 1 NatalHC.pdf: 2764921 bytes, checksum: 846252ab05f6de9b65d1cf7bbe1aba09 (MD5) Previous issue date: 2008-08-04 / In this work we propose a technique that uses uncontrolled small format aerial images, or SFAI, and stereohotogrammetry techniques to construct georeferenced mosaics. Images are obtained using a simple digital camera coupled with a radio controlled (RC) helicopter. Techniques for removing common distortions are applied and the relative orientation of the models are recovered using projective geometry. Ground truth points are used to get absolute orientation, plus a definition of scale and a coordinate system which relates image measures to the ground. The mosaic is read into a GIS system, providing useful information to different types of users, such as researchers, governmental agencies, employees, fishermen and tourism enterprises. Results are reported, illustrating the applicability of the system. The main contribution is the generation of georeferenced mosaics using SFAIs, which have not yet broadly explored in cartography projects. The proposed architecture presents a viable and much less expensive solution, when compared to systems using controlled pictures / No presente trabalho, descrevemos uma metodologia para a constru??o de mosaicos georreferenciados a partir de imagens a?reas de pequeno formato, ou SFAI, consideradas n?o controladas. T?cnicas de Est?reo-Fotogrametria e de Vis?o Computacional s?o aplicadas para auxiliarem em resultados de qualidade e confiabilidade. As imagens s?o obtidas atrav?s de uma c?mera digital comum acoplada a um helic?ptero aeromodelo. T?cnicas para eliminar distor??es comuns s?o aplicadas e a orienta??o relativa dos modelos ? realizada baseada na geometria projetiva. Pontos reais do terreno s?o usados para executar a orienta??o absoluta, al?m de uma defini??o de escala e de um sistema de coordenadas que relaciona a imagem medida no terreno. O mosaico ser? manipulado em um SIG, fornecendo informa??o ?til a diferentes tipos de usu?rios, tais como pesquisadores, institui??es governamentais, pescadores e empresas de turismo. Resultados s?o gerados, ilustrando a aplicabilidade do sistema. A principal contribui??o ? a gera??o de mosaicos georreferenciados usando imagens a?reas de pequeno formato, o que tem sido pouqu?ssimo explorado em projetos de cartografia. A arquitetura proposta apresenta uma solu??o vi?vel e bem barata quando comparada com sistemas que utilizam imagens controladas

Submitted by Marlene Santos (marlene.bc.ufg@gmail.com) on 2018-11-05T18:46:12Z No. of bitstreams: 2 Dissertação - Dyego Oliveira Almeida - 2018.pdf: 32110237 bytes, checksum: 4d30b2227be666802bbb2e5437450fc2 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2018-11-06T10:03:22Z (GMT) No. of bitstreams: 2 Dissertação - Dyego Oliveira Almeida - 2018.pdf: 32110237 bytes, checksum: 4d30b2227be666802bbb2e5437450fc2 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-11-06T10:03:22Z (GMT). No. of bitstreams: 2 Dissertação - Dyego Oliveira Almeida - 2018.pdf: 32110237 bytes, checksum: 4d30b2227be666802bbb2e5437450fc2 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2018-10-03 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / The urban growth of the population and the deforestation of greenareas are one of the most critical problems currently in Brazil. Due to mobilization of rural people to the urban, high solar irradiation and the deforestation, the Government is creating sustainable actions sustainable in order to enlarge the green areas and permeable. In this perspective, to promote this mapping effectively in large areas necessary to the use of technologies of recognition of facial features. Low-resolution satellite imagery have low cost and great coverage area coverage, and therefore apply them in identifying features is advantageous over other types of images. However, to accomplish this identification is computationally complex due to the different features present in images of this type. This work proposes an effective method of digital processing of low resolution images in the identification of features, in particular the pertinent green aáreas with average accuracy of 80.5% and detection of buildings with an average accuracy of 63%. / O crescimento urbano da população e o desmatamento de áreas verdes são um dos problemas mais críticos atualmente no Brasil. Devido a mobilização da população rural para o âmbito urbano, elevação da irradiação solar e o desmatamento, o governo está criando ações sustentáveis a fim de ampliar as áreas verdes e permeáveis. Nesta perspectiva, para promover esse mapeamento de forma eficaz em grandes áreas se faz necessário o uso de tecnologias de reconhecimento de feições. Imagens de satélite de baixa resolução possuem baixo custo e grande abrangência de área, e portanto aplicá-las na identificação de feições é vantajoso em relação a outros tipos de imagens. No entanto, realizar essa identificação é computacionalmente complexo devido as diferentes características existentes em imagens desse tipo. Este trabalho propõe um método eficaz de processamento digital de imagens de baixa resolução na identificação de feições, em particular as pertinentes a áreas verdes com acurácia média de 80,5% e detecção de edificações com precisão média de 63%.

台灣位於環太平洋地震帶上，地形為山地居多，且地質脆弱，加上位於西太平洋副熱帶地區，使得山區常受到颱風的侵擾而發生崩塌，導致土石流和洪水等災害發生，進而影響人民的生命和財產安全。因此，如何有效地建置崩塌地區域資料庫，成為國土保育與災害防治的重要課題。以往利用遙測與航測技術於崩塌地萃取的研究中，大多是於幾何糾正後衛星影像或是航測正射影像上分析崩塌地，但產製正射影像或是糾正衛星影像時，都需要花費較多的時間，對於講求時效性的救災行動而言頗為不利。本研究之目的為發展一套不需使用正射影像萃取崩塌地的方法，以物件導向影像分類法，於DMC（Digital Mapping Camera）航測原始影像上直接萃取崩塌地資訊。首先採取多重解析影像分割的技術，將航測影像依像元光譜和形狀同質性分割成不同區塊（物件），接著利用影像光譜統計值搭配區域成長法，偵測影像中的雲覆蓋地區並過濾。其次，根據光譜亮度統計特徵值，將影像區分成陰暗地區、正常地區以及較亮地區之三種土地覆蓋類型，使用線性相關糾正法（Linear-correlation Correction）將陰暗地區光譜亮度值轉換至正常地區，並利用物件的特徵值，如光譜、面積、形狀以及相關性依序萃取此三種土地覆蓋類型內的崩塌地。最後，使用光線追蹤法 （Ray-tracing），將崩塌地區塊從影像坐標轉換至地圖坐標，使其可以套疊地形資料如坡度、坡向，並進行空間分析以提升崩塌地的判釋精度。研究結果顯示，崩塌地萃取之使用者精度和生產者精度，均有82%以上，並且整個實驗可大量批次處理影像，及快速建立崩塌地資料庫，本研究之方法和崩塌地資料庫將有助於國土保育與崩塌地的災害防治。 / Being located in a subtropical and seismic zone of the West Pacific, the geology is fragile and topography is mountainous in Taiwan. Landslides, floods and other disasters induced by typhoons occur frequently, and it cause the life-threatening and property loss of human beings in Taiwan. Therefore, how to establish landslides data effectively become an important issue of land conservation and disasters management. In recently years, most of the researchers used aerial ortho-images or satellite georeferencing images to detect landslides sites. However, it spent a lot of time generating aerial ortho-images and rectifying satellite images, and it also reduced the efficiency of landslides analysis. Thus, this study developed an object-oriented classification method, which can be directly applied in raw image data, to detect landslides sites. Firstly, this study used multi-resolution image segmentation technique to segment images acquired by Z/I DMC（Digital Mapping Camera） into individual regions （objects） according to the homogeneity of spectral and shape features, and then removed cloud areas by using brightness features depended on the spectral information of images. Secondly, the study divided the entire image into three areas, which are darker area, normal area and lighter area, according to brightness value. Next, Linear-correlation correction （LCC） method was used in this study to transform darker area to normal area so that it can easily detect the landslides sites in darker area, and the object features, such as spectral, area, shape and space correlation indices, were used to extract landslide sites in images. Finally, in order to enhance the accuracy of landslide, the initial landslides were converted from image coordinate system to map coordinate system by ray-tracing method, so the initial landslides data can be further extracted by using topographic data, including slope and aspect data. The results of this study showed that the user and producer accuracies of detecting landslides can reach up to 82%. Moreover, the entire experiments process of this study can batch analyze automatically and establish landslides database quickly. It is expected that the method and landslides data of this study may have contribution to land conservation and disasters management.

近來三維數值城市及數碼城市（Cyber City）為各界極欲發展及研究的課題，為了要增加三維數值城市的擬真性及美觀程度，通常是將建物模型敷貼真實拍攝之牆面影像，增加三維模型的細緻化程度。而欲精確的敷貼牆面紋理影像，必須嚴密地將所拍攝之近景影像定位定向，一般採用光束法區域平差解算，此時需加上適當的控制點控制資訊才能完成，因此控制點控制資訊若來自地面測量將相當耗費成本。多年來，各地方政府製作大比例尺地形圖時已拍攝相當多的航照影像，可用來做為上述的控制資訊，亦即航空影像控制實體，若能使用這些航空影像控制實體作為控制資訊，不但可有效利用資源，亦能減少控制點取得所需花費的成本。因此，本研究將使用航空影像控制實體所提供的控制資訊做為控制來源。 本研究探討以航空影像控制實體作為控制資訊時，使用非量測型相機以類似傳統航測拍攝方式及旋轉多基線交向拍攝方式拍攝涵蓋建物牆面的目標區影像後，於最少控制且不同控制分布時，對光束法區域平差精度之影響。因使用非量測型相機，故本研究先以iWitnessPRO近景攝影測量軟體率定相機參數，接著以PHIDIAS近景攝影測量軟體解算光束法區域平差。過程中探討使用航空影像控制實體作為控制資訊時，於最少控制且不同控制分布時，加入附加參數解算的自率光束法區域平差與與一般光束法區域平差之精度。根據實驗結果，低樓層取像的光束法區域平差之檢核點RMSE精度，其結果大多可應用於LOD 3精度等級的牆面敷貼。另，因都市地區高樓林立，狹小巷弄多，有鑒於此，本研究使用旋轉多基線交向攝影，結果顯示其將有機會運用於近景攝影測量LOD 3精度等級的牆面紋理敷貼。 / Recently, the studies about the cyber city have become a popular topic. For improving the level of detail of cyber city, photo-realistic textures from images are mapped onto the surfaces of 3D building models. Before the accurate texture mapping, bundle block adjustment can be performed to recover the parameters of exterior orientation for each close-range images more accurate and more precise, where the control information is necessary. For the past years, many aerial photogrammetry projects were done by local governments for the mapping of 1/1000 topographic maps. Those historic aerial images can be used as control information to reduce the cost and increase the efficiency. Therefore, this study investigates the accuracy of bundle block adjustment about non-metric close-range images, taken from the ways similar to the traditional aerial photogrammetry and the rotating multi-baseline photogrammetry, by using control entities from historic aerial images as the minimal controls under various control distributions. Since the non-metric camera is used for collecting the close-range images, the iWitnessPRO software is utilized for camera calibration. After that, the PHIDIAS software, a close-range photogrammetry software, is employed to performed the bundle block adjustment. During performing the bundle block adjustment, the camera parameters are regarded as unknowns and determined, called as self-calibration bundle adjustment. The results of self-calibration bundle adjustment will be compared with conventional bundle adjustment. The test results show that the accuracy of most self-calibration bundle adjustment about close-range images covered with low buildings can be used for the application of LOD 3 texture mapping. Moreover, the test results of using close-range images from rotating multi-baseline photogrammetry in urban areas show the potential possibility for LOD 3 texture mapping in urban areas with high buildings and narrow alleys.