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Developing fixed-point photography methodologies for assessing post-fire mountain fynbos vegetation succession as a tool for biodiversity managementAlkalei, Osama January 2020 (has links)
Magister Scientiae (Biodiversity and Conservation Biology) - MSc (Biodiv and Cons Biol) / Areas of high biodiversity and complex species assemblages are often difficult to manage and to set up meaningful monitoring and evaluations programmes. Mountain Fynbos is such an ecosystem and in the Cape of Good Hope (part of the Table Mountain National Park) plant biodiversity over the last five decades has been in decline. The reasons are difficult to speculate since large herbivores, altered fire regimes and even climate change could be contributors to this decline which has been quantified using fixed quadrats and standard cover-abundance estimates based on a Braun-Blanquet methodology. To provide more detailed data that has more resolution in terms of identifying ecological processes, Fixed-Point Repeat Photography has been presented as a management “solution”. However, photography remains a difficult method to standardize subjects and has certain operational limitations.
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Reconstruction of 3D scenes from pairs of uncalibrated images : creation of an interactive system for extracting 3D data points and investigation of automatic techniques for generating dense 3D data maps from pairs of uncalibrated images for remote sensing applicationsAlkhadour, Wissam Mohamad January 2010 (has links)
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.
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Reconstruction of 3D scenes from pairs of uncalibrated images. Creation of an interactive system for extracting 3D data points and investigation of automatic techniques for generating dense 3D data maps from pairs of uncalibrated images for remote sensing applications.Alkhadour, Wissam M. January 2010 (has links)
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.
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Desenvolvimento de método para inferência de características físicas da água associadas às variações espectrais. Caso de Estudo: Reservatório de Itupararanga/SPPereira, Adriana Castreghini de Freitas [UNESP] 28 November 2008 (has links) (PDF)
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pereira_acf_dr_prud.pdf: 5065860 bytes, checksum: cf34424bad6a80c07230f80a12e3567a (MD5) / Na sociedade atual, discussões relacionadas à água potável tem ocupado um espaço importante, principalmente no meio científico, onde, através de pesquisas voltadas à disponibilidade e qualidade das águas é possível preparar diagnósticos e apontar soluções para planejadores e tomadores de decisões. Nesse contexto, o objetivo geral do trabalho foi desenvolver um método para inferência de variáveis limnológicas que indicam a qualidade da água e estejam associadas à sua característica espectral, em um reservatório de uso múltiplo e avaliar sua correlação com dados espectrais tomados “in situ” e extraídos de imagens orbitais de satélites de alta resolução espacial. Para tanto, uma imagem multiespectral do satélite Ikonos II foi adquirida, quase simultaneamente a coleta de dados limnológicos e espectrais “in situ”, em pontos amostrados adequadamente no corpo d’água, e posicionados com GPS. Devido à heterogeneidade das condições do tempo no levantamento de campo, uma nova abordagem amostral foi necessária, que se deu pela divisão da amostra em quatro conjuntos, quais foram: conjunto 1 (céu aberto e vento fraco), conjunto 2 (céu aberto e vento de médio a forte), conjunto 3 (céu nublado e vento fraco) e conjunto 4 (céu nublado e vento de médio a forte)... / In current society, drinkable water has been the subject of innumerable debates, mainly in scientific groups, in which, through researches focused on the availability and water quality, it is possible to prepare diagnoses and point out solutions to planners and decision makers. In this context, the general aim of the research was to develop a method for the inference of physical limnological variables that indicate the quality of the water and that are associated to its spectral characteristic, in a multiple use reservoir and evaluate its correlation to spectral data collected in situ and extracted from orbital images of high definition space sattelites. In order to achieve that, a multispectral image of the satellite Ikonos II was acquired, almost simultaneously to the gathering of limnological and spectral data “in situ”, in points sampled adequately in the water surveyed, and positioned by means of GPS. Due to the heterogeneous weather conditions when taking the ground samples, a new sampling approach was necessary, and it occurred with the division of the sample in four settings, which were: setting 1 (clear sky and mildly windy), setting 2 (clear sky and windy), setting 3 (overcast sky and mildly windy) and setting 4 (overcast sky and windy)... (Complete abstract click electronic access below)
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Desenvolvimento de método para inferência de características físicas da água associadas às variações espectrais. Caso de Estudo: Reservatório de Itupararanga/SP /Pereira, Adriana Castreghini de Freitas. January 2008 (has links)
Resumo: Na sociedade atual, discussões relacionadas à água potável tem ocupado um espaço importante, principalmente no meio científico, onde, através de pesquisas voltadas à disponibilidade e qualidade das águas é possível preparar diagnósticos e apontar soluções para planejadores e tomadores de decisões. Nesse contexto, o objetivo geral do trabalho foi desenvolver um método para inferência de variáveis limnológicas que indicam a qualidade da água e estejam associadas à sua característica espectral, em um reservatório de uso múltiplo e avaliar sua correlação com dados espectrais tomados "in situ" e extraídos de imagens orbitais de satélites de alta resolução espacial. Para tanto, uma imagem multiespectral do satélite Ikonos II foi adquirida, quase simultaneamente a coleta de dados limnológicos e espectrais "in situ", em pontos amostrados adequadamente no corpo d'água, e posicionados com GPS. Devido à heterogeneidade das condições do tempo no levantamento de campo, uma nova abordagem amostral foi necessária, que se deu pela divisão da amostra em quatro conjuntos, quais foram: conjunto 1 (céu aberto e vento fraco), conjunto 2 (céu aberto e vento de médio a forte), conjunto 3 (céu nublado e vento fraco) e conjunto 4 (céu nublado e vento de médio a forte)... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: In current society, drinkable water has been the subject of innumerable debates, mainly in scientific groups, in which, through researches focused on the availability and water quality, it is possible to prepare diagnoses and point out solutions to planners and decision makers. In this context, the general aim of the research was to develop a method for the inference of physical limnological variables that indicate the quality of the water and that are associated to its spectral characteristic, in a multiple use reservoir and evaluate its correlation to spectral data collected "in situ" and extracted from orbital images of high definition space sattelites. In order to achieve that, a multispectral image of the satellite Ikonos II was acquired, almost simultaneously to the gathering of limnological and spectral data "in situ", in points sampled adequately in the water surveyed, and positioned by means of GPS. Due to the heterogeneous weather conditions when taking the ground samples, a new sampling approach was necessary, and it occurred with the division of the sample in four settings, which were: setting 1 (clear sky and mildly windy), setting 2 (clear sky and windy), setting 3 (overcast sky and mildly windy) and setting 4 (overcast sky and windy)... (Complete abstract click electronic access below) / Orientador: Maria de Lourdes Bueno Trindade Galo / Coorientador: Edivaldo Domingues Velin / Banca: Cláudio Clemente Faria Barbosa / Banca: Waterloo Pereira Filho / Banca: Renata Ribeiro de Araújo / Banca: Vilma Mayumi Tachibana / Doutor
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[en] KNOWLEDGE-BASED INTERPRETATION OF HIGH RESOLUTION REMOTE SENSING IMAGES / [pt] INTERPRETAÇÃO BASEADA EM CONHECIMENTO DE IMAGENS DE SENSORES REMOTOS DE ALTA RESOLUÇÃOTHIAGO BROERMAN CAZES 21 March 2006 (has links)
[pt] A cada dia mais e mais satélites de alta resolução têm se
tornado disponíveis,
criando grande demanda por novos métodos de interpretação
baseados em
conhecimento. Estes métodos emulam parcialmente o trabalho
do especialista em
análise visual de imagens. Nesse contexto, o presente
trabalho apresenta um modelo de
classificação baseado no conhecimento do especialista
aplicado a imagens de alta
resolução. O modelo de interpretação consiste de três
fases. A primeira inclui o
conhecimento espectral e a informação de textura. Na
segunda fase dados de SIG
(sistema de informação geográfico) são combinados com o
resultado da análise
espectral através de regras nebulosas. Na terceira e
última fase é introduzido o
conhecimento multitemporal através de uma estimativa das
possibilidades de transição
entre classes de uma mesma área em um dado intervalo de
tempo. Para validação desse
modelo experimentos foram realizados em imagens IKONOS e
fotos aéreas de 1999,
2001 e de 2002 da área do Parque Estadual da Pedra Branca,
que é um importante
fragmento da Floresta Atlântica situado no estado do Rio
de Janeiro, Brasil. / [en] New high resolution satellites for commercial purposes
became available in the
few years. This increases the need of new automatic
knowledge based image
interpretation methods. Such methods partially emulate the
reasoning of an image
analyst during the visual image interpretation. The
present work falls into this context
and proposes an automatic classification model for high
resolution remotely sensed
images. The model consists of three stages. In the first
stage only spectral and textural
information are used for classification. In the second
stage GIS (geographic information
system) data are combined with the result of the spectral
analysis by means of fuzzy
rules. In the third stage the multitemporal knowledge is
introduced by estimating class
transition possibilities within a given time span. To
validate the proposed model
experiments were performed based on IKONOS images from
2001 and 2002 as well as
aerial photos from 1999 of the Pedra Branca Park, which is
an important Atlantic Forest
fragment in the State Rio de Janeiro in Southeast Brazil.
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Augmenting High-Dimensional Data with Deep Generative Models / Högdimensionell dataaugmentering med djupa generativa modellerNilsson, Mårten January 2018 (has links)
Data augmentation is a technique that can be performed in various ways to improve the training of discriminative models. The recent developments in deep generative models offer new ways of augmenting existing data sets. In this thesis, a framework for augmenting annotated data sets with deep generative models is proposed together with a method for quantitatively evaluating the quality of the generated data sets. Using this framework, two data sets for pupil localization was generated with different generative models, including both well-established models and a novel model proposed for this purpose. The unique model was shown both qualitatively and quantitatively to generate the best data sets. A set of smaller experiments on standard data sets also revealed cases where this generative model could improve the performance of an existing discriminative model. The results indicate that generative models can be used to augment or replace existing data sets when training discriminative models. / Dataaugmentering är en teknik som kan utföras på flera sätt för att förbättra träningen av diskriminativa modeller. De senaste framgångarna inom djupa generativa modeller har öppnat upp nya sätt att augmentera existerande dataset. I detta arbete har ett ramverk för augmentering av annoterade dataset med hjälp av djupa generativa modeller föreslagits. Utöver detta så har en metod för kvantitativ evaulering av kvaliteten hos genererade data set tagits fram. Med hjälp av detta ramverk har två dataset för pupillokalisering genererats med olika generativa modeller. Både väletablerade modeller och en ny modell utvecklad för detta syfte har testats. Den unika modellen visades både kvalitativt och kvantitativt att den genererade de bästa dataseten. Ett antal mindre experiment på standardiserade dataset visade exempel på fall där denna generativa modell kunde förbättra prestandan hos en existerande diskriminativ modell. Resultaten indikerar att generativa modeller kan användas för att augmentera eller ersätta existerande dataset vid träning av diskriminativa modeller.
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