Fast unsupervised technique for extraction of endmembers spectra from hyperspectral data

One of the most challenging task underlying many hyperspectral imagery applications is the linear unmixing. The key to linear unmixing is to find the set of reference substances, also called endmembers, that are representative of a given scene. This paper presents the vertex component analysis (VCA) a new method to unmix linear mixtures of hyperspectral sources. The algorithm is unsupervised and exploits a simple geometric fact: endmembers are vertices of a simplex. The algorithm complexity, measured in floating points operations, is O (n), where n is the sample size. The effectiveness of the proposed scheme is illustrated using simulated data.

Advanced image processing techniques for detection and quantification of drusen

Dissertation presented to obtain the degree of Doctor of Philosophy in Electrical Engineering, speciality on Perceptional Systems, by the Universidade Nova de Lisboa, Faculty of Sciences and Technology

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

Parallel sparse unmixing of hyperspectral data

In this paper, a new parallel method for sparse spectral unmixing of remotely sensed hyperspectral data on commodity graphics processing units (GPUs) is presented. A semi-supervised approach is adopted, which relies on the increasing availability of spectral libraries of materials measured on the ground instead of resorting to endmember extraction methods. This method is based on the spectral unmixing by splitting and augmented Lagrangian (SUNSAL) that estimates the material's abundance fractions. The parallel method is performed in a pixel-by-pixel fashion and its implementation properly exploits the GPU architecture at low level, thus taking full advantage of the computational power of GPUs. Experimental results obtained for simulated and real hyperspectral datasets reveal significant speedup factors, up to 1 64 times, with regards to optimized serial implementation.

Fast unsupervised extraction of endmembers spectra from hyperspectral data

Linear unmixing decomposes an hyperspectral image into a collection of re ectance spectra, called endmember signatures, and a set corresponding abundance fractions from the respective spatial coverage. This paper introduces vertex component analysis, an unsupervised algorithm to unmix linear mixtures of hyperpsectral data. VCA exploits the fact that endmembers occupy vertices of a simplex, and assumes the presence of pure pixels in data. VCA performance is illustrated using simulated and real data. VCA competes with state-of-the-art methods with much lower computational complexity.

Comparison of Disposable Pipette Extraction and Dispersive Solid-Phase Extraction in the QuEChERS Method for Analysis of Pesticides in Strawberries

In this study, we sought to assess the applicability of GC–MS/MS for the identification and quantification of 36 pesticides in strawberry from integrated pest management (IPM) and organic farming (OF). Citrate versions of QuEChERS (quick, easy, cheap, effective, rugged and safe) using dispersive solid-phase extraction (d-SPE) and disposable pipette extraction (DPX) for cleanup were compared for pesticide extraction. For cleanup, a combination of MgSO4, primary secondary amine and C18 was used for both the versions. Significant differences were observed in recovery results between the two sample preparation versions (DPX and d-SPE). Overall, 86% of the pesticides achieved recoveries (three spiking levels 10, 50 and 200 µg/kg) in the range of 70–120%, with <13% RSD. The matrix effects were also evaluated in both the versions and in strawberries from different crop types. Although not evidencing significant differences between the two methodologies were observed, however, the DPX cleanup proved to be a faster technique and easy to execute. The results indicate that QuEChERS with d-SPE and DPX and GC–MS/MS analysis achieved reliable quantification and identification of 36 pesticide residues in strawberries from OF and IPM.

Utilização de métodos ópticos de correlação de imagem para a determinação da tenacidade à fractura de adesivos estruturais

Mestrado em Engenharia Mecânica

Estudo da importância do transporte ferroviário de mercadorias no Eixo Leixões- Salamanca

A evolução dos transportes de mercadorias, em Portugal e na União Europeia, assume uma enorme repercussão na economia global, de modo que a combinação dos vários modos de transporte, com vista à obtenção de ganhos ao nível da eficiência, adquire extrema importância. Os programas europeus de apoio aos transportes, enquadrados na rede transeuropeia de transportes e plataformas logísticas, também contribuem para a otimização do transporte de mercadorias. A importância do transporte ferroviário de mercadorias no eixo Leixões- Salamanca, nomeadamente para as empresas exportadoras e importadoras da região norte e centro, que utilizam meios alternativos ao ferroviário, constitui o principal objetivo desta dissertação. A revisão bibliográfica inclui uma abordagem aos transportes de mercadorias em geral e de forma mais aprofundada aos modos ferroviário e rodoviário na península ibérica, passando pela logística, bem como pela integração de modos: intermodalidade e multimodalidade na rede europeia de transportes e ainda a referência aos portos secos e às plataformas logísticas. Isto permite caraterizar as diferentes empresas operadoras do setor dos transportes de mercadorias e os produtos transacionados, assim como enumerar vantagens e/ou desvantagens do meio de transporte ferroviário face a outros meios, mais concretamente no eixo alvo deste estudo. A metodologia utilizada consiste na análise de informação proveniente de fontes secundárias havendo lugar a uma referência mais detalhada sobre as plataformas logísticas de Leixões e Salamanca, o eixo E-80, o corredor ferroviário nº4 e os programas europeus promotores da eficiência no transporte ferroviário de mercadorias: Marathon, Ferremed e Marco Polo. Para a recolha de informação primária o instrumento adotado foi a entrevista semiestruturada, efetuada a dois representantes da empresa CP-Carga e a um representante da empresa KLog, ambas as empresas ligadas ao setor dos transportes e logística. A análise e tratamento de toda a informação recolhida possibilitam, desde logo, evidenciar as potencialidades do eixo Leixões-Salamanca no que se refere ao transporte ferroviário de mercadorias, delinear recomendações para a sua otimização, bem como efetuar uma análise SWOT. As considerações finais revelam que é imperativo adotar medidas, de forma integrada, para que o seu efeito na potenciação do transporte ferroviário de mercadorias, não só no eixo Leixões-Salamanca, mas também a nível europeu, se afirme como uma verdadeira alternativa a outros modos, particularmente ao domínio rodoviário.

Georeferencing Road Accidents with Google Earth: Transforming Information into Knowledge for Decision Support

Over the last fifty years mobility practices have changed dramatically, improving the way travel takes place, the time it takes but also on matters like road safety and prevention. High mortality caused by high accident levels has reached untenable levels. But the research into road mortality stayed limited to comparative statistical exercises which go no further than defining accident types. In terms of sharing information and mapping accidents, little progress has been mad, aside from the normal publication of figures, either through simplistic tables or web pages. With considerable technological advances on geographical information technologies, research and development stayed rather static with only a few good examples on dynamic mapping. The use of Global Positioning System (GPS) devices as normal equipments on automobile industry resulted in a more dynamic mobility patterns but also with higher degrees of uncertainty on road traffic. This paper describes a road accident georeferencing project for the Lisbon District involving fatalities and serious injuries during 2007. In the initial phase, individual information summaries were compiled giving information on accidents and its majour characteristics, collected by the security forces: the Public Safety Police Force (Polícia de Segurança Pública - PSP) and the National Guard (Guarda Nacional Republicana - GNR). The Google Earth platform was used to georeference the information in order to inform the public and the authorities of the accident locations, the nature of the location, and the causes and consequences of the accidents. This paper also gives future insights about augmented reality technologies, considered crucial to advances to road safety and prevention studies. At the end, this exercise could be considered a success because of numerous consequences, as for stakeholders who decide what to do but also for the public awareness to the problem of road mortality.

Data Extraction Tool to Analyse, Transform and Store Real Data from Electricity Markets

The study of electricity markets operation has been gaining an increasing importance in the last years, as result of the new challenges that the restructuring process produced. Currently, lots of information concerning electricity markets is available, as market operators provide, after a period of confidentiality, data regarding market proposals and transactions. These data can be used as source of knowledge to define realistic scenarios, which are essential for understanding and forecast electricity markets behavior. The development of tools able to extract, transform, store and dynamically update data, is of great importance to go a step further into the comprehension of electricity markets and of the behaviour of the involved entities. In this paper an adaptable tool capable of downloading, parsing and storing data from market operators’ websites is presented, assuring constant updating and reliability of the stored data.

An automatic tool to Extract, Transform and Load data from real electricity markets

The study of Electricity Markets operation has been gaining an increasing importance in the last years, as result of the new challenges that the restructuring produced. Currently, lots of information concerning Electricity Markets is available, as market operators provide, after a period of confidentiality, data regarding market proposals and transactions. These data can be used as source of knowledge, to define realistic scenarios, essential for understanding and forecast Electricity Markets behaviour. The development of tools able to extract, transform, store and dynamically update data, is of great importance to go a step further into the comprehension of Electricity Markets and the behaviour of the involved entities. In this paper we present an adaptable tool capable of downloading, parsing and storing data from market operators’ websites, assuring actualization and reliability of stored data.

Algorithms for time series clustering applied to biomedical signals

Thesis submitted in the fulfillment of the requirements for the Degree of Master in Biomedical Engineering

Imagiologia Espetral - Análise Forense de Notas e Escrita Manual

A análise forense de documentos é uma das áreas das Ciências Forenses, responsável pela verificação da autenticidade dos documentos. Os documentos podem ser de diferentes tipos, sendo a moeda ou escrita manual as evidências forenses que mais frequentemente motivam a análise. A associação de novas tecnologias a este processo de análise permite uma melhor avaliação dessas evidências, tornando o processo mais célere. Esta tese baseia-se na análise forense de dois tipos de documentos - notas de euro e formulários preenchidos por escrita manual. Neste trabalho pretendeu-se desenvolver técnicas de processamento e análise de imagens de evidências dos tipos referidos com vista a extração de medidas que permitam aferir da autenticidade dos mesmos. A aquisição das imagens das notas foi realizada por imagiologia espetral, tendo-se definidas quatro modalidades de aquisição: luz visível transmitida, luz visível refletida, ultravioleta A e ultravioleta C. Para cada uma destas modalidades de aquisição, foram também definidos 2 protocolos: frente e verso. A aquisição das imagens dos documentos escritos manualmente efetuou-se através da digitalização dos mesmos com recurso a um digitalizador automático de um aparelho multifunções. Para as imagens das notas desenvolveram-se vários algoritmos de processamento e análise de imagem, específicos para este tipo de evidências. Esses algoritmos permitem a segmentação da região de interesse da imagem, a segmentação das sub-regiões que contém as marcas de segurança a avaliar bem como da extração de algumas características. Relativamente as imagens dos documentos escritos manualmente, foram também desenvolvidos algoritmos de segmentação que permitem obter todas as sub-regiões de interesse dos formulários, de forma a serem analisados os vários elementos. Neste tipo de evidências, desenvolveu-se ainda um algoritmo de análise para os elementos correspondentes à escrita de uma sequência numérica o qual permite a obtenção das imagens correspondentes aos caracteres individuais. O trabalho desenvolvido e os resultados obtidos permitiram a definição de protocolos de aquisição de imagens destes tipos de evidências. Os algoritmos automáticos de segmentação e análise desenvolvidos ao longo deste trabalho podem ser auxiliares preciosos no processo de análise da autenticidade dos documentos, o qual, ate então, é feito manualmente. Apresentam-se ainda os resultados dos estudos feitos às diversas evidências, nomeadamente as performances dos diversos algoritmos analisados, bem como algumas das adversidades encontradas durante o processo. Apresenta-se também uma discussão da metodologia adotada e dos resultados, bem como de propostas de continuação deste trabalho, nomeadamente, a extração de características e a implementação de classificadores capazes aferir da autenticidade dos documentos.

Automated image tagging through tag propagation

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial Para obtenção do grau de Mestre em Engenharia Informática

Sistema de apoio à navegação baseado em automatic identification system

Dissertação de Mestrado Integrado em Engenharia Electrotécnica e Computadores