Made available in DSpace on 2014-06-11T19:22:25Z (GMT). No. of bitstreams: 0 Previous issue date: 2009-03-26Bitstream added on 2014-06-13T20:28:44Z : No. of bitstreams: 1 langhi_pjp_me_prud.pdf: 4558873 bytes, checksum: 6633a0b385f223c9200a10403ba4fa9b (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / As diferenças radiométricas entre áreas homólogas de imagens aéreas digitais são causadas por vários fatores e afetam os processos fotogramétricos, como a correspondência e a mosaicagem. Para que as imagens possam ser melhoradas, alguns procedimentos como correção geométrica e radiométrica são aplicados, sendo a correção radiométrica o tema de estudo deste trabalho. O processo de correção radiométrica em imagens aéreas digitais tem como principal objetivo tornar semelhantes os histogramas de imagens que possuam sobreposição, facilitando os processos posteriores de correspondência de pontos homólogos e a formação de mosaicos. O método proposto neste trabalho realiza em duas etapas a correção radiométrica para um bloco de imagens aéreas digitais. A primeira etapa é um processamento global, baseado nos dados dos histogramas. A segunda etapa é uma correção local, que pode ser realizada através de dois métodos estudados, sendo que o primeiro trata a interpolação dos valores de correção à partir de regiões homólogas, possibilitando a correção radiométrica da região de sobreposição das imagens; e o segundo método utiliza o ajuste de uma superfície parabolóide às diferenças radiométricas entre imagens, fornecendo, posteriormente, valores de correção para toda a imagem. Para realizar os processos descritos acima, foi implementado um programa em linguagem C, o qual realiza o ajuste local a partir de pontos correspondentes. Alguns experimentos foram realizados, utilizando três blocos de imagens aéreas obtidas com câmeras digitais Hasselblad de 22 e 39 megapixels, respectivamente, os quais apresentaram resultados satisfatórios. / Radiometric differences between homologous areas in digital aerial imagens are caused by several factors and affect the photogrammetric processes like correspondence and mosaicking. In order to enhance those images, some procedures like geometric and radiometric corrections can be applied, the last being the aim of this work. The process of radiometric adjustment in digital aerial images aim at to make similar the histograms of overlapping images, favoring the processes of correspondence and mosaicking formation. The method proposed in this work is performed in two stages: firstly a global processing based on the histograms data and secondly a local strategy, for which two methods were studied. The first is an interpolation of correction values corresponding to the radiometric differences in the overlapping images. The second method for the local adjustment uses surface adjustment in order to correct the differences in the corresponding regions. In order to assess the proposed methodology, a program in C language was implemented to perform the local adjustment based on some corresponding points. Some experiments were accomplished, using three blocks of aerial images taken with 22 and 39 megapixels digital cameras, and good results were achieved.

Background. The view of the Earth from above can offer a lot of data and with technological advancements in image sensors and high-resolution satellite images there is more quantity and quality of data which can be useful in research and applications like military, monitoring climate, etc. Deep neural networks have been successful in object detection and it is seen that their learning process can be improved with using right hyperparameters when configuring the networks. This can be done hyperparameter optimization by the use of genetic algorithms. Objectives. The thesis focuses on obtaining deep learning techniques with optimal hyperparameters using genetic algorithm to detect aircraft, vehicles and ships from satellite and aerial images and compare the optimal models with the original deep learning models. Methods. The study uses literature review to obtain the appropriate deep learning techniques for object detection in satellite and aerial images, followed by conducting experiments in order to implement a genetic algorithm to find the right hyperparameters and then followed by another experiment which compares the performance between optimal and original deep learning model on basis of performance metrics mentioned in the study. Results. The literature review results depict that deep learning techniques for object detection in satellite and aerial images are Faster R-CNN, SSD and YOLO. The results of experiments show that the genetic algorithm was successful in finding optimal hyperparameters. The accuracy achieved by optimized models was higher than the original models in the case of aircraft, vehicles and ship detection. The results also show that the training times for the models have been reduced with the use of optimal hyperparameters with slight decrease in precision when detecting ships. Conclusions. After analyzing all the results carefully, the best deep learning techniques to detect aircraft, vehicles and ships are found and stated. The implementation of the genetic algorithm has been successful as it provided a set of hyperparameters which resulted in the improvement of accuracy, precision and recall in all scenarios except for values of precision in ship detection as well as improvement in training times.

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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.

Um mosaico é o conjunto de fotos de uma determinada área, recortadas e montadas técnica e artísticamente, de forma a dar a impressão de que todo o conjunto é uma única fotografia. No caso de fotografias aéreas, sua utilização soluciona o problema da necessidade de se retratar uma área de interesse mais extensa do que o campo de cobertura das lentes da câmera utilizada. O foco deste trabalho é a criação automática de mosaicos buscando encontrar a posição real de um conjunto de imagens imagens adquiridas em baixa altitude, de baixa escala, em relação à um Mapa de Base, de escala maior, realizando, assim, uma correlação entre imagens de escalas diferentes. Este problema é abordado por técnicas de análise multi-escala, mais precisamente, pela utilização de filtros de Gabor. A metodologia desenvolvida utiliza um banco de filtros de Gabor aplicado sobre uma imagem de referência de modo que, a partir da aplicação destes filtros sobre a mesma, seja possível gerar um processo automático de geração do mosaico para o restante do conjunto de imagens. Experimentos realizados utilizando o método proposto demonstram a eficácia do mesmo para imagens com texturas de orientação marcante, como o caso de imagens aéreas de plantação de eucaliptos / A mosaic is a set of pictures of a given area, technically and artistically cut and ?glued? together, giving the impression that the entire set resembles a single picture. For aerial photography, the use of mosaics solves the problem of imaging an area of interest whose dimension is much larger than that covered by the majority of the cameras available. This work focuses on the automatic creation of mosaics and aims to compute the real position of a set of images acquired at low altitudes (lower scale), in relation with a base map larger scale), by correlating images in different scales. Multi-scale analysis techniques, in particular, the Gabor filters, constitute an approach to this problem. The proposed methodology uses a bank of Gabor filters applied over a reference image in a way that an automatic process of mosaic generation, with the remaining set of images, could be carried out. Experiments have shown the efficiency of the proposed technique especially for images with clear textural orientation, for example, the case of aerial photographs of eucalyptus plantations

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In this study, a new approach for the matching and reconstruction of line features from multispectral stereo aerial images is presented. The advantages of the existing multispectral information in aerial images are fully taken into account all over the steps of pre-processing and edge detection. To accurately describe the straight line segments, a principal component analysis technique is adapted. The initial correspondences between the stereo images are generated using a new pair-wise stereo matching approach which involves a total of seven relational constraints. The final line to line correspondences between the stereo images are established in a precise matching stage in which the final line matches are assigned by means of three novel measures and a final similarity voting scheme. Once the line matches are established, the stereo reconstruction of those matches is performed by an innovative reconstruction approach that manipulates the redundancy inherent in line pair-relations. By this way, the reconstruction of the stereo matches that are observed in a nearly-parallel geometry with the epipolar lines can also be performed accurately. The proposed approach is tested over two different urban test sites with various built-up characteristics, and as a result, very successful and promising stereo line matching and reconstruction performances are reached. Besides, the comparison of the results of the proposed approach with the results of one of the state-of-the-art stereo matching approaches proves the superiority and the potential of proposed approach.

Resumo: Este trabalho propõe uma nova metodologia para extração de rodovias utilizando imagens aéreas digitais. A inovação baseia-se no algoritmo de Programação dinâmica (PD), que nesta metodologia realiza o processo de otimização no espaço objeto, e não no espaço imagem como as metodologias tradicionais de extração de rodovias por PD. A feição rodovia é extraída no espaço objeto, o qual implica um rigoroso modelo matemático, que é necessário para estabelecer os pontos entre o espaço imagem e objeto. Necessita-se que o operador forneça alguns pontos sementes no espaço imagem para descrever grosseiramente a rodovia, e estes pontos devem ser transformados para o espaço objeto para inicialização do processo de otimização por PD. Esta metodologia pode operar em diferentes modos (modo mono e estéreo), e com diversos tipos de imagens, incluindo imagens multisensores. Este trabalho apresenta detalhes da metodologia mono e estéreo e também os experimentos realizados e os resultados obtidos. / Abstract: This work proposes a novel road extraction methodology from digital images. The innovation is based on the dynamic programming (DP) algorithm to carry out the optimisation process in the object space, instead of doing it in the image space such as the DP traditional methodologies. Road features are traced in the object space, which implies that a rigorous mathematical model is necessary to be established between image and object space points. It is required that the operator measures a few seed points in the image space to describe sparsely and coarsely the roads, which must be transformed into the object space to make possible the initialisation of the DP optimisation process. Although the methodology can operate in different modes (mono-plotting or stereoplotting), and with several image types, including multisensor images, this work presents details of our single and stereo image methodology, along with the experimental results. / Orientador: João Fernando Custódio da Silva / Coorientador: Aluir Porfírio Dal Poz / Banca: Júlio Kiyoshi Hasegawa / Banca: Messias Meneguette Júnior / Doutor

Um mosaico é o conjunto de fotos de uma determinada área, recortadas e montadas técnica e artísticamente, de forma a dar a impressão de que todo o conjunto é uma única fotografia. No caso de fotografias aéreas, sua utilização soluciona o problema da necessidade de se retratar uma área de interesse mais extensa do que o campo de cobertura das lentes da câmera utilizada. O foco deste trabalho é a criação automática de mosaicos buscando encontrar a posição real de um conjunto de imagens imagens adquiridas em baixa altitude, de baixa escala, em relação à um Mapa de Base, de escala maior, realizando, assim, uma correlação entre imagens de escalas diferentes. Este problema é abordado por técnicas de análise multi-escala, mais precisamente, pela utilização de filtros de Gabor. A metodologia desenvolvida utiliza um banco de filtros de Gabor aplicado sobre uma imagem de referência de modo que, a partir da aplicação destes filtros sobre a mesma, seja possível gerar um processo automático de geração do mosaico para o restante do conjunto de imagens. Experimentos realizados utilizando o método proposto demonstram a eficácia do mesmo para imagens com texturas de orientação marcante, como o caso de imagens aéreas de plantação de eucaliptos / A mosaic is a set of pictures of a given area, technically and artistically cut and ?glued? together, giving the impression that the entire set resembles a single picture. For aerial photography, the use of mosaics solves the problem of imaging an area of interest whose dimension is much larger than that covered by the majority of the cameras available. This work focuses on the automatic creation of mosaics and aims to compute the real position of a set of images acquired at low altitudes (lower scale), in relation with a base map larger scale), by correlating images in different scales. Multi-scale analysis techniques, in particular, the Gabor filters, constitute an approach to this problem. The proposed methodology uses a bank of Gabor filters applied over a reference image in a way that an automatic process of mosaic generation, with the remaining set of images, could be carried out. Experiments have shown the efficiency of the proposed technique especially for images with clear textural orientation, for example, the case of aerial photographs of eucalyptus plantations

Orientador: Aluir Porfírio Dal Poz / Resumo: Neste trabalho foi proposta uma metodologia para a extração de contornos de telhados de edifícios no espaço-objeto, a partir da integração de um estéreo par de imagens aéreas de alta resolução e modelos 3D aproximados de telhado obtidos a partir de dados de varredura a LASER. Um modelo matemático considerando as propriedades radiométricas e geométricas dos telhados foi formulado a fim de representar o contorno do telhado no espaçoimagem, tendo como base o modelo de contorno ativo Snake. Esse modelo foi então adaptado para descrever os contornos no espaço-objeto considerando um estéreo par de imagens aéreas. Finalmente, o polígono ótimo que representa um dado contorno do telhado foi determinado a partir da otimização, via Programação Dinâmica, da função de energia criada. A solução obtida é uma representação mais acurada para o correspondente contorno do modelo 3D do telhado. O método desenvolvido apresenta também mecanismos para realizar a compensação automática de três tipos de problemas comuns em ambientes urbanos e que podem prejudicar a extração automática de telhados: obstruções perspectivas causadas por edifícios elevados, obstruções diretas causadas por vegetação que se eleva acima do telhado e sombras adjacentes aos telhados, as quais podem ser confundidas com as bordas do telhado. Os experimentos foram realizados utilizando imagens aéreas com GSD ≈ 0,10 m e nuvem de pontos LASER com densidade média de 6 pontos/m2. Os resultados mostraram que o método funciona adequad... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: In this work a methodology was proposed for extracting building roof contours in the object-space, by integration of a high-resolution aerial images stereo pair and 3D roof models reconstructed from LASER scanning data. A mathematical model considering the radiometric and geometric properties of roofs was developed in order to represent the roof contour in the image-space, based on the Snake active contour model. Then, the model was adapted to represent the contours in the object space considering a stereo pair of aerial images. Finally, the optimal polygon representing a selected roof contour was obtained by optimizing the proposed energy function using Dynamic Programming algorithm. The solution obtained, i.e., a polygon representing each 3D roof contour, will be a higher accurate representation for the correspondent contour of the 3D roof model. The proposed method also presents mechanisms to perform the compensation of three types of common problems in urban environment and which can disturb the automatic roof extraction: perspective occlusions caused by high buildings, occlusions caused by vegetation that covers the roof and shadows that are adjacent to the roofs which can be misinterpreted as roof edges. The experiments were performed using aerial images with GSD ≈ 0,10 m and LASER point cloud with average density of 6 points/m2. The results showed that the proposed method works properly in contour extraction of roofs with occlusion and shadows areas, presenting complet... (Complete abstract click electronic access below) / Doutor