O Processamento e Análise Digital de Imagens é utilizado cada vez mais para agilizar processos, aumentar a precisão, segurança e confiabilidade de dados extraídos de imagens nas mais diversas áreas de pesquisa. No entanto, muitas vezes é necessário que o pesquisador faça, ele próprio, o pré-processamento das imagens, mesmo não sendo um especialista nesta área. Isto coloca em risco o próprio objetivo do uso do Processamento e Análise Digital de Imagens. Este trabalho analisa a relação dos dados extraídos de uma imagem (micrografia) através do software livre ImageJ com relação ao seu processamento final desejado, avaliando assim, a necessidade ou não, de uma ou mais sequencias de pré-processamento para adequar a imagem para o processamento final, indicando ainda quais fatores de influência apresentam informações irrelevantes ou incompletas para o processamento final utilizando ferramentas da Lógica Paraconsistente Anotada. Os resultados obtidos mostram que esta abordagem carece de informações diversificadas sobre a imagem original capturada que possam subsidiar a tomada de decisão quanto aos procedimentos necessários e, para o pré-processamento adequado ao objetivo desejado. / Processing and Analysis of Digital Images is increasingly used to streamline processes, improve accuracy, safety and reliability of data extracted from images in various research areas. However, it is often necessary for the researcher to make himself, the preprocessing of images, although not an expert in this area. This puts at risk the very purpose of using the Processing and Analysis of Digital Images. This paper analyzes the relationship of the data extracted from an image (micrograph) through the free software ImageJ, with respect to its desired final processing. Thus, evaluating the necessity or not, of one or more sequences of preprocessing to adjust the image to the final processing, further indicating which factors influence presents incomplete or irrelevant information for final processing using tools of Annotaded Paraconsistent Logic. The results show that this approach lacks diversified information about the original image captured that can support decision making about procedures for appropriate preprocessing to the desired goal.

Orientador: Yuzo Iano / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-05T13:46:30Z (GMT). No. of bitstreams: 1 Silva_FernandoSilvestreda_D.pdf: 35017484 bytes, checksum: fb460a6a42e44fe0a50e94599ac027fc (MD5) Previous issue date: 2005 / Resumo: A excelente qualidade visual e taxa de compressão dos codificadores fractais de imagem tem aplicações limitadas devido ao exaustivo tempo de codificação inerente. Esta pesquisa apresenta um novo codificador híbrido de imagens que aplica a velocidade da transformada wavelet à qualidade da compressão fractal. Neste esquema, uma codificação fractal acelerada usando a classificação de domínios de Fisher é aplicada na sub-banda passa-baixas de uma imagem transformada por wavelet e uma versão modificada do SPIHT (Set Partitioned in Hierarchical Trees) é aplicada nos coeficientes remanescentes. Os detalhes de imagem e as características de transmissão progressiva da transformada wavelet são mantidas; nenhum efeito de bloco comuns às técnicas fractais é introduzido, e o problema de fidelidade de codificação comuns aos codificadores híbridos fractal-wavelet é resolvido. O sistema proposto reduz o tempo médio de processamento das imagens em 94% comparado com o codificador fractal tradicional e um ganho de 0 a 2,4dB em PSNR sobre o algoritmo SPIHT puro. Em ambos os casos, o novo esquema proposto apresentou melhorias em temos de qualidade subjetiva das imagens para altas, médias e baixas taxas de compressão / Abstract: The excellent visual quality and compression rate of fractal image coding have limited applications due to exhaustive inherent encoding time. This research presents a new fast and efficient image coder that applies the speed of the wavelet transform to the image quality of the fractal compression. In this scheme, a fast fractal encoding using Fisher¿s domain classification is applied to the lowpass subband of wavelet transformed image and a modified SPIHT coding (Set Partitioning in Hierarchical Trees), on the remaining coefficients. The image details and wavelet progressive transmission characteristics are maintained; no blocking effects from fractal techniques are introduced; and the encoding fidelity problem common in fractal-wavelet hybrid coders is solved. The proposed scheme provides an average of 94% reduction in encoding-decoding time compared to the pure accelerated Fractal coding results, and a 0-2,4dB gain in PSNR over the pure SPIHT coding. In both cases, the new scheme improves the subjective quality of pictures for high, medium and low bit rates / Doutorado / Telecomunicações e Telemática / Doutor em Engenharia Elétrica

Made available in DSpace on 2015-04-11T14:03:02Z (GMT). No. of bitstreams: 1 Ruan Josemberg Silva Belem.pdf: 270710 bytes, checksum: 6becb4184530c335870aefc5042c2116 (MD5) Previous issue date: 2006-05-12 / Fundação de Amparo à Pesquisa do Estado do Amazonas / The World Wide Web is a huge source of diverse information, including offensive material such as pornography related content. This poses the problem of automatcally detecting offensive content as a way to avoid unauthorised access, for instance, by children or by employees during working hours. Although this sort of information is published in many forms, including text, sound and video, images are the most common form of publication of offensive content on the Web. Detecting offensive images can be considered as a classification problem. Given that images are part of Web pages, textual information can be used as important evidence along with the content extracted from images, such as colour, texture and shapes. This dissertation proposes two distinct approaches for automatic detection of offensive images on the Web. The first is based on image content, specifically colour. The second approach is based on textual terms extracted from the Web page that present the images. After evidence extraction the classification is performed using the SVM technique, based on a collection of 1000 offensive images and 1000 non-offensive images for training. Experiments carried out have shown that both approaches are effective, although they rely on simple algorithms for extracting evidences related to the images. / A World Wide Web (Web) é uma fonte de informação com grande quantidade e diversidade de conteúdo, incluindo material de caráter ofensivo relacionado á pornografia. Diante deste cenário, existe a necessidade de detectar tal conteúdo ofensivo de maneira a evitar que o mesmo seja indevidamente acessado por crianças ou por funcionários de empresas, onde o acesso a este tipo de conteúdo geralmente não é permitido. Embora este tipo de informação possa estar presente na Web em forma de texto, vídeo ou sons, grande parte deste conteúdo está disponibilizado na forma de imagens. O problema de identificação de imagens ofensivas pode ser visto como um problema de classificação. Como as imagens em questão estão inseridas em páginas web, além das informações que podem ser extraídas da própria imagem, também têm-se as informações textuais encontradas nas páginas que possuem as imagens. Aptos a extração de evidências a classificação é realizada usando-se um classificador baseado em SVM treinado com uma coleção de 1000 imagens ofensivas e 1000 imagens não-ofensivas. Este trabalho apresenta duas abordagens diferentes para detecção de imagens ofensivas na Web: a primeira, baseada no conteúdo da imagem e a segunda, baseada em evidências textuais extraídas das páginas web onde se encontram as imagens. Ambas as abordagens se mostraram efiazes na detecção de imagens ofensivas, apesar de utilizarem algoritmos simples para a extração de informações relacionadas às imagens.

<p>Problemi klasifikacije i segmentacije digitalnih slika su veoma<br />aktuelni i zastupljeni u praksi. Potreba za modelima koji razmatraju<br />ovu problematiku u poslednjih nekoliko decenija ubrzanim tempom<br />poprima sve veći značaj i obim u svakodnevnom životu. Koriste se u<br />računarskoj grafici, prepoznavanju oblika, medicinskoj analizi slika,<br />saobraćaju, analizi dokumenata, pokreta i izraza lica i sl.<br />U okviru ove disertacije, predstavljeno istraživanje motivisano je<br />primenama razvijenih modela u klasifikaciji i segmentaciji<br />digitalnih slika. Istraživanje obuhvata dva segmenta. Ovi segmenti<br />povezani su terminom neodređenosti, koji je uz upotrebu adekvatnog<br />matematičkog aparata (teorije fazi skupova), ugrađen u modele razvije<br />za primenu u obradi slike.<br />Jedan pravac istraživanja baziran je na teoriji fazi skupova, t-<br />normama, t-konormama, operatorima agregacije i agregiranim<br />funkcijama rastojanja. U okviru toga, istraživanje je sprovedeno sa<br />struktuiranom matematičkom podlogom, izložene su osnovne<br />definicije, teoreme, kao i osobine korištenih operatora, prošireni<br />su teorijski koncepti t-normi i t-konormi. Definisani su novi tipovi<br />operatora agregacije i njihovom primenom konstruisane su nove<br />funkcije rastojanja, čija je upotreba diskutovana kroz uspešnost u<br />procesu segmentacije digitalnih slika.<br />Drugi pravac istraživanja, izložen u ovoj disertaciji, obuhvata više<br />inženjerski pristup rešavanju problema klasifikacije tekstura<br />digitalnih slika. U skladu sa tim, detaljno je analizirana i<br />diskutovana klasa lokalnih binarnih deskriptora teksture.<br />Inspirisana uspešnošću pomenute LBP klase deskriptora, uvedena je<br />jedna nova podfamilija &alpha;-deskriptora teksture. Uvedeni model<br />deskriptora formiran je na temeljima idejnih principa lokalnih<br />binarnih kodova i bazičnih pojmova iz teorije fazi skupova. Praktična<br />upotreba i značaj predstavljenog modela demonstrirani su kroz veoma<br />uspešne procese klasifikacije na nekoliko javno dostupnih baza slika.</p> / <p>Classification and segmentation problems of digital images is a very attractive<br />topic and has been making impact in many different applied disciplines. In the<br />past few decades, the demand for models that address these issues has been<br />gaining momentum and applications in everyday life. These models are used in<br />computer graphics, shape recognition, medical image analysis, traffic, document<br />analysis, facial movements and expressions, etc.<br />The research within this doctoral dissertation was motivated by the application of<br />developed methods in classification and segmentation tasks. The conducted<br />research covered two segments, which were linked by the term of indeterminacy,<br />with the usage of the theory of fuzzy sets, which is incorporated into methods<br />developed for application in image processing.<br />One direction of the research was founded on the theory of fuzzy sets, t-norms,<br />t-conorms, aggregation operators, and aggregated distance functions. Within this<br />framework, the research was conducted with a structured mathematical<br />background. Firstly, basic definitions, theorems and characteristics of the used<br />operators were presented, followed by the theoretical concepts of t-norms and tconorms<br />that were extended. New types of aggregation operators and distance<br />functions were defined, and finally, their contribution in the digital image<br />segmentation process was explored and discussed.<br />The second direction of the research presented in this dissertation involved more<br />of an engineering-type of approach to solving the problem of the classification of<br />digital image textures. To that end, a class of local binary texture descriptors<br />(LBPs) was analyzed and discussed in detail. Inspired by the results of the<br />above-mentioned LBP descriptors, one new sub-family of the $\alpha$-<br />descriptors was introduced by the author. The introduced descriptor model was<br />based on the conceptual principles of LBPs and basic definitions from the fuzzy<br />set theory. Its practical usage and importance were established and reflected in<br />very successful classification results, achieved in the application on several<br />publicly available image datasets.</p>

El presente proyecto, propone la implementación de un algoritmo computacional de detección de equipos de protección personal (EPP) orientado a sistemas de vigilancia basados en Cámaras IP. El algoritmo propuesto realizará el monitoreo autónomo de los EPP de cabeza y manos, disminuyendo los riesgos laborales y cuidando la salud de los trabajadores que ejecuten las actividades. El sistema propuesto utiliza algoritmos de visión artificial para procesar las imágenes capturadas por las cámaras de video vigilancia de la empresa. En una primera etapa, se utiliza la red neuronal Open Pose para extraer las imágenes de brazos y cabeza de los trabajadores. Después, las imágenes son procesadas por redes neuronales convolucionales entrenadas para clasificar la existencia de los EPP mencionados. El sistema será aplicado a la realidad de la empresa Distribución Eléctrica S.A, donde se implementará un software que permita a los usuarios finales visualizar las alertas generadas por el algoritmo, así como recibir las alertas mediante su correo electrónico. Los resultados obtenidos por el sistema de clasificación serán evaluados utilizando métricas como la precisión, sensibilidad y especificidad. / This project proposes the implementation of a computational algorithm for the detection of personal protective equipment (PPE) oriented to surveillance systems based on IP cameras. The proposed algorithm carried out the autonomous monitoring of head and hand PPE, reducing occupational risks and taking care of the health of the workers who carry out the activities. The proposed system uses artificial vision algorithms to process the images captured by the company's video surveillance cameras. In a first stage, the Open Pose neural network is used to extract the images of the workers' arms and heads. The images are then processed by convolutional neural networks trained to classify the existence of the mentioned EPPs. The system will be applied to the reality of the company Distribución Eléctrica S.A, where a software will be implemented that allows end users to view the alerts generated by the algorithm, as well as receive the alerts through their email. The results obtained by the classification system will be evaluated using metrics such as precision, sensitivity, and specificity. / Tesis

The thesis is aimed at movement analysis and planning of a robotic device for absolute GNSS antenna calibration, which is developed at Brno University of Technology, Faculty of Civil Engineering, Institute of Geodesy. The first section is devoted to independent verification of the temporal synchronization of the robotic device’s movement, which is a prerequisite for the successful antenna calibration. The following section is focused on analysis of moveable characteristics since their knowledge is crucial for the following movement planning. Method of the device’s movement shooting by camera and evaluation its position based on gained photographs is used for both testing measurements. The final part is dedicated to movement planning, especially to calibrated antenna weighting influence on device’s movement characteristics, test results implementation into the observation program and arm movement planning considering the homogeneous calibration measurement layout.

Kompozitní materiály se projevují komplexním způsobem porušování, které může být dále ovlivněno přítomností různých poruch plynoucích z výrobních processů nebo se vyskytujících v průběhu života součásti. Důkladné porozmění procesů porušování a jejich okolností je nezbytné pro navrhování kompozitních konstrukcí, jenž budou bezpečnější, trvanlivější a ekonomičtější. V první části disertační práce jsou popsány způsoby porušování kompozitů a uvedeny současné matematické metody pro analýzu a výpočet únosnosti. Dále jsou zde vyjmenovány hlavní druhy vad a stručně diskutován jejich vliv na vlastnosti kompozitních materiálů. Zvláštní důraz je kladen na delaminace, společně se základními principy lomové mechaniky a jejich uplatnění při výpočtech a zkoušení kompozitů. Druhá část je zaměřena na delaminace na rozhranní dvou různých materialů. Lomová houževnatost byla experimantálně měřena ve třech typech zatížení za účelem stanovení poruchového kritéria založeného na podílu módu I a módu II. Během tohoto experimentu byla vyvinuta nová metoda měření délky trhliny pomocí digitáního zpracování obrazu a rovněž byla navržena nová definice počátku šíření trhliny. Analytické vztahy pro výpočet míry uvolnění deformační energie z naměřených dat byly rozšířeny o vliv rozdílných elastické parametrů materiálů na rozhranní. Podrobnější prozkoumání analytických vztahů a výpočet metodou konečných prvků odhalil, že podíl módu I a módu II je závislý na vzdálenosti od čela trhliny a poruchové kritérium založené na podílu smíšenosti tak nemůže být použito.

El presente trabajo desarrolla un sistema automático que permite el conteo y medición de una población de alevines de tilapia gris. En la actualidad, existen muchos procesos encargados del cálculo de las dimensiones geométricas de los alevines que tienen una gran subjetividad y requieren mucho tiempo para ser ejecutados. Además, la extracción de los alevines fuera del agua puede causarles estrés, lo que podría llevarlos a la muerte. De esta manera, se busca erradicar la intervención manual, por lo que se elabora una estructura mecánica que sostiene una pecera y un recinto con iluminación y una segunda pecera transparente. Se realiza un traslado por muestras de alevines del primer al segundo recipiente, para ello se utilizan las rejillas controladas por motores para acercarlos o alejarlos del orificio de desfogue de la primera pecera. Asimismo, se utiliza una electroválvula neumática de bola, que funciona como compuerta que permite o deniega el paso de los alevines por la tubería de PVC. Luego, con los alevines en el recinto, se procede a ejecutar los algoritmos de conteo y medición de largo y ancho. Se obtuvieron resultados satisfactorios porque el sistema tiene una precisión del 98% en el conteo y del 90% en la medición de largo y ancho. Además, el tiempo para el cálculo de ambos parámetros se redujo en comparación con el proceso manual. / The present work develops an automatic system that allows the counting and the measuring of a population of gray tilapia fingerlings. Nowadays, there are many processes in charge of the calculation of the geometric dimensions of the fingerlings that have a great subjectivity and spend a lot of time. In addition, removing the fingerlings from the water can cause stress to them, which it could lead them to death. In this way, it seeks to eradicate the manual intervention, thus a mechanical structure is elaborated which holds a fish tank and an enclosure with illumination and a second transparent tank. A transfer by samples of fingerlings from the first to the second container is carried out, for this purpose the grids controlled by motors are used to bring them closer or move them away from the bleed orifice of the first container. Also, a ball pneumatic electrovalve is used, which works as a gate that allows or forbid the passage of the fingerlings through the PVC pipe. Then, with the fingerlings in the enclosure, it proceeds to execute the counting and measuring algorithms of length and width. Satisfactory results were obtained because it has an accuracy of 98% in counting and 90% in length and width measuring. Furthermore, the time for the calculation of both parameters were reduced in comparison to the manual process. / Tesis

Sand and mud traversed by tidal inlets and channels, which split in subtle branches, salt marshes at the coast, the tide, harsh weather conditions and a high diversity of fauna and flora characterize the ecosystem Wadden Sea. No other landscape on the Earth changes in such a dynamic manner. Therefore, land cover classification and monitoring of vulnerable ecosystems is one of the most important approaches in remote sensing and has drawn much attention in recent years. The Wadden Sea in the southeastern part of the North Sea is one such vulnerable ecosystem, which is highly dynamic and diverse. The tidal flats of the Wadden Sea are the zone of interaction between marine and terrestrial environments and are at risk due to climate change, pollution and anthropogenic pressure. Due to that, the European Union has implemented various directives, which formulate objectives such as achieving or maintaining a good environmental status respectively a favourable conservation status within a given time. In this context, a permanent observation for the estimation of the ecological condition is needed. Moreover, changes can be tracked or even foreseen and an appropriate response is possible. Therefore, it is important to distinguish between short-term changes, which are related to the dynamic manner of the ecosystem, and long-term changes, which are the result of extraneous influences. The accessibility both from sea and land is very poor, which makes monitoring and mapping of tidal flat environments from in situ measurements very difficult and cost-intensive. For the monitoring of big areas, time-saving applications are needed. In this context, remote sensing offers great possibilities, due to its provision of a large spatial coverage and non-intrusive measurements of the Earth’s surface. Previous studies in remote sensing have focused on the use of electro-optical and radar sensors for remote sensing of tidal flats, whereas microwave systems using synthetic aperture radar (SAR) can be a complementary tool for tidal flat observation, especially due to their high spatial resolution and all-weather imaging capability. Nevertheless, the repetitive tidal event and dynamic sedimentary processes make an integrated observation of tidal flats from multi-sourced datasets essential for mapping and monitoring. The main challenge for remote sensing of tidal flats is to isolate the sediment, vegetation or shellfish bed features in the spectral signature or backscatter intensity from interference by water, the atmosphere, fauna and flora. In addition, optically active materials, such as plankton, suspended matter and dissolved organics, affect the scattering and absorption of radiation. Tidal flats are spatially complex and temporally quite variable and thus mapping tidal land cover requires satellites or aircraft imagers with high spatial and temporal resolution and, in some cases, hyperspectral data. In this research, a hierarchical knowledge-based decision tree applied to multi-sensor remote sensing data is introduced and the results have been visually and numerically evaluated and subsequently analysed. The multi-sensor approach comprises electro-optical data from RapidEye, SAR data from TerraSAR-X and airborne LiDAR data in a decision tree. Moreover, spectrometric and ground truth data are implemented into the analysis. The aim is to develop an automatic or semi-automatic procedure for estimating the distribution of vegetation, shellfish beds and sediments south of the barrier island Norderney. The multi-sensor approach starts with a semi-automatic pre-processing procedure for the electro-optical data of RapidEye, LiDAR data, spectrometric data and ground truth data. The decision tree classification is based on a set of hierarchically structured algorithms that use object and texture features. In each decision, one satellite dataset is applied to estimate a specific class. This helps to overcome the drawbacks that arise from a combined usage of all remote sensing datasets for one class. This could be shown by the comparison of the decision tree results with a popular state-of-the-art supervised classification approach (random forest). Subsequent to the classification, a discrimination analysis of various sediment spectra, measured with a hyperspectral sensor, has been carried out. In this context, the spectral features of the tidal sediments were analysed and a feature selection method has been developed to estimate suitable wavelengths for discrimination with very high accuracy. The developed feature selection method ‘JMDFS’ (Jeffries-Matusita distance feature selection) is a filter-based supervised band elimination technique and is based on the local Euclidean distance and the Jeffries-Matusita distance. An iterative process is used to subsequently eliminate wavelengths and calculate a separability measure at the end of each iteration. If distinctive thresholds are achieved, the process stops and the remaining wavelengths are applied in the further analysis. The results have been compared with a standard feature selection method (ReliefF). The JMDFS method obtains similar results and runs 216 times faster. Both approaches are quantitatively and qualitatively evaluated using reference data and standard methodologies for comparison. The results show that the proposed approaches are able to estimate the land cover of the tidal flats and to discriminate the tidal sediments with moderate to very high accuracy. The accuracies of each land cover class vary according to the dataset used. Furthermore, it is shown that specific reflection features can be identified that help in discriminating tidal sediments and which should be used in further applications in tidal flats.

Das Buch gibt eine Einführung in die Digitale Bildverarbeitung. Der Inhalt des Buches gliedert sich in sechs Kapitel. Im ersten Kapitel werden die wichtigsten Definitionen und Anwendungsgebiete der Digitalen Bildverarbeitung sowie wesentliche Komponenten eines digitalen Bildverarbeitungssystems erklärt. Das zweite Kapitel befasst sich mit den Grundlagen digitaler Bilder, den Bilddatenformaten und Kompressionsverfahren. Die Grundlagen der Farbtheorie und ein kurzer Überblick über die wichtigsten Farbsysteme werden im dritten Kapitel vermittelt. Die zwei anschließenden Kapitel beschäftigen sich mit der Manipulation von Grauwerten. Der Schwerpunkt liegt hier auf den Punktoperationen und den Filtertechniken. Das letzte Kapitel behandelt die für die Lehrgebiete Photogrammetrie, Fernerkundung und Geoinformationssysteme überaus wichtigen Grundlagen der geometrischen Transformation.:Vorwort 1. Einführung in die digitale Bildverarbeitung 1.1 Definition der Bildverarbeitung 1.2 Anwendungsgebiete der Digitalen Bildverarbeitung 1.3 Komponenten eines Bildverarbeitungssystems 2. Digitale Bilder 2.1 Entstehung digitaler Bilder 2.2 Bildmatrix und Grauwerte 2.3 Digitale Bilder im Ortsbereich 2.3.1 Bildrepräsentation 2.3.2 Auflösung eines Pixels 2.3.3 Das Pixelkoordinatensystem 2.3.4 Grundsätzliche Festlegungen 2.3.5 Topologien oder Nachbarschaftsrelationen 2.3.6 Distanzen 2.4 Eigenschaften digitaler Bilder 2.4.1 Mittelwert und mittlere quadratische Abweichung 2.4.2 Varianz und Standardabweichung 2.4.3 Histogramm 2.4.4 Stochastische Einflüsse 2.5 Kompressionen und Datenformate 2.5.1 Ausgewählte Verfahren zur Bildkompression 2.5.2 Bilddatenformate 3. Farbtheorie 3.1 Was ist Farbe? 3.2 Farbsysteme 3.2.1 RGB- und CMY- Farbsystem 3.2.2 Das Farbdreieck (Maxwell’sches Dreieck) 3.2.3 Das IHS- Modell 3.2.4 Das CIE- Farbmodell 3.3 Bildwiedergabe 3.4 Farbmanipulation 4. Punktoperationen 4.1 Schwellwertoperation zur Erzeugung von Binärbildern 4.2 Arithmetische Bildoperationen 4.3 Logische oder Boolesche Kombinationen 4.4 Kontrast- und Helligkeitsänderungen 4.4.1 Kontrastübertragungsfunktionen 4.4.2 Kontrastveränderung durch Histogrammanpassungen 4.4.3 Äquidensitenherstellung 5. Filteroperationen 5.1 Lineare Filter 5.1.1 Tiefpassfilter 5.1.2 Hochpassfilter 5.1.2.5 Schärfung 5.2 Morphologische Filter 5.2.1 Medianfilter 5.2.2 Minimum- und Maximumfilter 5.2.3 Dilatation und Erosion im Binärbild 5.2.4 Opening und Closing 6. Geometrische Bildtransformationen 6.1 Koordinatentransformationen im 2D-Raum 6.2 Direkte und indirekte Transformation 6.2.1 Direkte Transformation 6.2.2 Indirekte Transformation 6.3 Resampling 6.3.1 Nächster Nachbar 6.3.2 Bilineare Interpolation 6.3.3 Interpolationen höherer Ordnung 6.3.4 Zusammenfassung der Interpolationsmethoden Quellennachweis Sachregister / The book provides an introduction into digital image processing. The content of the book is divided into six chapters. In the first chapter, the most important definitions and areas of application of digital image processing as well as essential components of a digital image processing system are explained. The second chapter deals with the basics of digital images, image data formats and compression methods. The basics of color theory and a brief overview of the most important color systems are presented in the third chapter. The following two chapters deal with the manipulation of gray values. The focus here is on point operations and filtering techniques. The last chapter deals with the fundamentals of geometric transformation, which are extremely important for the areas of photogrammetry, remote sensing and geographic information systems.:Vorwort 1. Einführung in die digitale Bildverarbeitung 1.1 Definition der Bildverarbeitung 1.2 Anwendungsgebiete der Digitalen Bildverarbeitung 1.3 Komponenten eines Bildverarbeitungssystems 2. Digitale Bilder 2.1 Entstehung digitaler Bilder 2.2 Bildmatrix und Grauwerte 2.3 Digitale Bilder im Ortsbereich 2.3.1 Bildrepräsentation 2.3.2 Auflösung eines Pixels 2.3.3 Das Pixelkoordinatensystem 2.3.4 Grundsätzliche Festlegungen 2.3.5 Topologien oder Nachbarschaftsrelationen 2.3.6 Distanzen 2.4 Eigenschaften digitaler Bilder 2.4.1 Mittelwert und mittlere quadratische Abweichung 2.4.2 Varianz und Standardabweichung 2.4.3 Histogramm 2.4.4 Stochastische Einflüsse 2.5 Kompressionen und Datenformate 2.5.1 Ausgewählte Verfahren zur Bildkompression 2.5.2 Bilddatenformate 3. Farbtheorie 3.1 Was ist Farbe? 3.2 Farbsysteme 3.2.1 RGB- und CMY- Farbsystem 3.2.2 Das Farbdreieck (Maxwell’sches Dreieck) 3.2.3 Das IHS- Modell 3.2.4 Das CIE- Farbmodell 3.3 Bildwiedergabe 3.4 Farbmanipulation 4. Punktoperationen 4.1 Schwellwertoperation zur Erzeugung von Binärbildern 4.2 Arithmetische Bildoperationen 4.3 Logische oder Boolesche Kombinationen 4.4 Kontrast- und Helligkeitsänderungen 4.4.1 Kontrastübertragungsfunktionen 4.4.2 Kontrastveränderung durch Histogrammanpassungen 4.4.3 Äquidensitenherstellung 5. Filteroperationen 5.1 Lineare Filter 5.1.1 Tiefpassfilter 5.1.2 Hochpassfilter 5.1.2.5 Schärfung 5.2 Morphologische Filter 5.2.1 Medianfilter 5.2.2 Minimum- und Maximumfilter 5.2.3 Dilatation und Erosion im Binärbild 5.2.4 Opening und Closing 6. Geometrische Bildtransformationen 6.1 Koordinatentransformationen im 2D-Raum 6.2 Direkte und indirekte Transformation 6.2.1 Direkte Transformation 6.2.2 Indirekte Transformation 6.3 Resampling 6.3.1 Nächster Nachbar 6.3.2 Bilineare Interpolation 6.3.3 Interpolationen höherer Ordnung 6.3.4 Zusammenfassung der Interpolationsmethoden Quellennachweis Sachregister