Wilhelm Burger

Wilhelm Burger
Fachhochschule Oberösterreich | fh-ooe · Digital Media

Dr.

About

212
Publications
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2,066
Citations
Citations since 2016
59 Research Items
1033 Citations
2016201720182019202020212022050100150
2016201720182019202020212022050100150
2016201720182019202020212022050100150
2016201720182019202020212022050100150
Introduction

Publications

Publications (212)
Chapter
Edge information is essential in many image analysis and computer vision applications and thus the ability to locate and characterize edges robustly and accurately is an important task. Basic techniques for edge detection in grayscale images are discussed in Chap. 5. Color images contain richer information than grayscale images and it appears natur...
Chapter
When we compare two images, we are faced with the following basic question: when are two images the same or similar, and how can this similarity be measured? Of course one could trivially define two images I1, I2 as being identical when all pixel values are the same (i.e., the difference I1−I2 is zero). Although this kind of definition may be usefu...
Chapter
Most feature detection schemes are based on local change or gradient information, for example, corner detection or SIFT features. In this sense MSER features are complementary since they rely on image regions, i.e., patches of connected pixels that exhibit some increased uniformity instead of change.
Chapter
Prominent image “events” originating from local changes in intensity or color, such as edges and contours, are of high importance for the visual perception and interpretation of images. The perceived amount of information in an image appears to be directly related to the distinctiveness of the contained structures and discontinuities. In fact, edge...
Chapter
Corners are prominent structural elements in an image and are therefore useful in a wide variety of applications, including following objects across related images (tracking), determining the correspondence between stereo images, serving as reference points for precise geometrical measurements, and calibrating camera systems for machine vision appl...
Chapter
This chapter addresses the problem of fitting circles to a given set of data points in 2D, which arises in numerous applications in engineering, medicine, physics, remote sensing, archeology, etc. Despite the classic nature of this problem, reliable and efficient algorithms have only been developed in the last few decades and are still a topic of a...
Chapter
The Fourier transform and the DFT are designed for processing complex-valued signals, and they always produce a complex-valued spectrum even in the case where the original signal was strictly real-valued. The reason is that neither the real nor the imaginary part of the Fourier spectrum alone is sufficient to represent (i.e., reconstruct) the signa...
Chapter
The correlation-based registration methods described in Chap. 23 are rigid in the sense that they provide for translation as the only form of geometric transformation and positioning is limited to whole pixel units. In this chapter we look at methods that are capable of registering a reference image under (almost) arbitrary geometric transformation...
Chapter
Common to all the filters and point operations described so far is the fact that they may change the intensity function of an image but the position of each pixel, and thus the geometry of the image, remains the same. The purpose of geometric operations, which are discussed in this chapter, is to deform an image by altering its geometry. Typical ex...
Chapter
In a binary image, pixels can take on exactly one of two values. These values are often thought of as representing the “foreground” and “background” in the image, even though these concepts often are not applicable to natural scenes. In this chapter we focus on connected regions in images and how to isolate and describe such structures.
Chapter
For a long time, using a computer to manipulate a digital image (i.e., digital image processing) was something performed by only a relatively small group of specialists who had access to expensive equipment. Usually this combination of specialists and equipment was only to be found in research labs, and so the field of digital image processing has...
Chapter
In any application that requires precise, reproducible, and device independent presentation of colors, the use of calibrated color systems is an absolute necessity. For example, color calibration is routinely used throughout the digital print work flow but also in digital film production, professional photography, image databases, etc. One may have...
Chapter
Color images are everywhere and filtering them is such a common task that it does not seem to require much attention at all. In this chapter, we describe how classical linear and nonlinear filters, which we covered before in the context of grayscale images (see Chap. 4), can be either used directly or adapted for the processing of color images. Oft...
Chapter
Histograms are used to depict image statistics in an easily interpreted visual format. With a histogram, it is easy to determine certain types of problems in an image, for example, it is simple to conclude if an image is properly exposed by visual inspection of its histogram. In fact, histograms are so useful that modern digital cameras often provi...
Chapter
Interpolation is the process of estimating the intermediate values of a sampled function or signal at continuous positions or the attempt to reconstruct the original continuous function from a set of discrete samples. In the context of geometric operations this task arises from the fact that discrete pixel positions in one image are generally not m...
Chapter
The following three chapters deal with the representation and analysis of images in the frequency domain, based on the decomposition of image signals into sine and cosine functions using the wellknown Fourier transform. Students often consider this a difficult topic, mainly because of its mathematical flavor and that its practical applications are...
Chapter
The Fourier transform is defined not only for 1D signals but for functions of arbitrary dimension. Thus, 2D images are nothing special from a mathematical point of view.
Chapter
Point operations perform a modification of the pixel values without changing the size, geometry, or local structure of the image. Each new pixel value b = Iʹ(u, v) depends exclusively on the previous value a = I(u, v) at the same position and is thus independent from any other pixel value, in particular from any of its neighboring pixels.
Chapter
The essential property of point operations (discussed in the previous chapter) is that each new pixel value only depends on the original pixel at the same position. The capabilities of point operations are limited, however. For example, they cannot accomplish the task of sharpening or smoothing an image (Fig. 4.1). This is what filters can do. They...
Chapter
Many real applications require the localization of reference positions in one or more images, for example, for image alignment, removing distortions, object tracking, 3D reconstruction, etc. We have seen that corner points1 can be located quite reliably and independent of orientation. However, typical corner detectors only provide the position and...
Chapter
Although techniques based on binary image regions have been used for a very long time, they still play a major role in many practical image processing applications today because of their simplicity and efficiency. To obtain a binary image, the first and perhaps most critical step is to convert the initial grayscale (or color) image to a binary imag...
Chapter
Many geometrical shapes, such as lines, circles, and ellipses, can be readily described by simple equations with only a few parameters. Since such geometric “primitives” often occur as part of man-made objects, they are especially useful features for analysis of these types of images (see Fig. 12.1).
Chapter
Noise reduction in images is a common objective in image processing, not only for producing pleasing results for human viewing but also to facilitate easier extraction of meaningful information in subsequent steps, for example, in segmentation or feature detection. Simple smoothing filters, such as the Gaussian filter (See Sec. 4.6.1.) and the filt...
Chapter
Color images are involved in every aspect of our lives, where they play an important role in everyday activities such as television, photography, and printing. Color perception is a fascinating and complicated phenomenon that has occupied the interests of scientists, psychologists, philosophers, and artists for hundreds of years [238, 246]. In this...
Chapter
The straight line is such a simple yet important concept in the context of image geometry. Images of virtually any man-made structure will contain lines and, on the other hand, straight lines are quite rare in natural images. In this chapter we first look at how we can describe lines mathematically and which parameterizations are best suited for ou...
Chapter
In the discussion of the median filter in Chap. 4 (Sec. 4.4.2), we noticed that this type of filter can somehow alter 2D image structures. Figure 7.1 illustrates once more how corners are rounded off, holes of a certain size are filled, and small structures, such as single dots or thin lines, are removed.
Technical Report
Full-text available
A compact listing of ImageJ's public Java API.
Technical Report
Full-text available
This report details the algorithmic steps involved in the well-known camera calibration method by Zhang and describes an associated open-source Java implementation that depends only upon the Apache Commons Math library. Key terms: Computer vision, camera calibration, Zhang's method, camera projection, imaging geometry, image rectification, Java imp...
Chapter
Histograms are used to depict image statistics in an easily interpreted visual format. With a histogram, it is easy to determine certain types of problems in an image, for example, it is simple to conclude if an image is properly exposed by visual inspection of its histogram. In fact, histograms are so useful that modern digital cameras often provi...
Chapter
For a long time, using a computer to manipulate a digital image (i.e., digital image processing) was something performed by only a relatively small group of specialists who had access to expensive equipment. Usually this combination of specialists and equipment was only to be found in research labs, and so the field of digital image processing has...
Chapter
Fourier descriptors are an interesting method for modeling 2D shapes that are described as closed contours. Unlike polylines or splines, which are explicit and local descriptions of the contour, Fourier descriptors are global shape representations, that is, each component stands for a particular characteristic of the entire shape. If one component...
Chapter
Interpolation is the process of estimating the intermediate values of a sampled function or signal at continuous positions or the attempt to reconstruct the original continuous function from a set of discrete samples. In the context of geometric operations this task arises from the fact that discrete pixel positions in one image are generally not m...
Chapter
In Chapter 6 we demonstrated how to use appropriately designed filters to detect edges in images. These filters compute both the edge strength and orientation at every position in the image. In the following sections, we explain how to decide (e.g., by using a threshold operation on the edge strength) if a curve is actually present at a given image...
Chapter
The essential property of point operations (discussed in the previous chapter) is that each new pixel value only depends on the original pixel at the same position. The capabilities of point operations are limited, however. For example, they cannot accomplish the task of sharpening or smoothing an image (Fig. 5.1). This is what filters can do. They...
Chapter
The task of color quantization is to select and assign a limited set of colors for representing a given color image with maximum fidelity. Assume, for example, that a graphic artist has created an illustration with beautiful shades of color, for which he applied 150 different crayons. His editor likes the result but, for some technical reason, inst...
Chapter
Many real applications require the localization of reference positions in one or more images, for example, for image alignment, removing distortions, object tracking, 3D reconstruction, etc. We have seen that corner points1 can be located quite reliably and independent of orientation. However, typical corner detectors only provide the position and...
Chapter
Noise reduction in images is a common objective in image processing, not only for producing pleasing results for human viewing but also to facilitate easier extraction of meaningful information in subsequent steps, for example, in segmentation or feature detection. Simple smoothing filters, such as the Gaussian filter1 and the filters discussed in...
Chapter
When we compare two images, we are faced with the following basic question: when are two images the same or similar, and how can this similarity be measured? Of course one could trivially define two images I 1, I 2 as being identical when all pixel values are the same (i.e., the difference I 1 – I 2 is zero). Although this kind of definition may be...
Chapter
Edge information is essential in many image analysis and computer vision applications and thus the ability to locate and characterize edges robustly and accurately is an important task. Basic techniques for edge detection in grayscale images are discussed in Chapter 6. Color images contain richer information than grayscale images and it appears nat...
Chapter
Color images are involved in every aspect of our lives, where they play an important role in everyday activities such as television, photography, and printing. Color perception is a fascinating and complicated phenomenon that has occupied the interests of scientists, psychologists, philosophers, and artists for hundreds of years [211, 217]. In this...
Chapter
Common to all the filters and point operations described so far is the fact that they may change the intensity function of an image but the position of each pixel, and thus the geometry of the image, remains the same. The purpose of geometric operations, which are discussed in this chapter, is to deform an image by altering its geometry. Typical ex...
Chapter
Until a few years ago, the image-processing community was a relatively small group of people who either had access to expensive commercial image-processing tools or, out of necessity, developed their own software packages. Usually such home-brew environments started out with small software components for loading and storing images from and to disk...
Chapter
The following three chapters deal with the representation and analysis of images in the frequency domain, based on the decomposition of image signals into sine and cosine functions using the wellknown Fourier transform. Students often consider this a difficult topic, mainly because of its mathematical flavor and that its practical applications are...
Chapter
In any application that requires precise, reproducible, and deviceindependent presentation of colors, the use of calibrated color systems is an absolute necessity. For example, color calibration is routinely used throughout the digital print work flow but also in digital film production, professional photography, image databases, etc. One may have...
Chapter
Color images are everywhere and filtering them is such a common task that it does not seem to require much attention at all. In this chapter, we describe how classical linear and nonlinear filters, which we covered before in the context of grayscale images (see Ch. 5), can be either used directly or adapted for the processing of color images. Often...
Chapter
Corners are prominent structural elements in an image and are therefore useful in a wide variety of applications, including following objects across related images (tracking), determining the correspondence between stereo images, serving as reference points for precise geometrical measurements, and calibrating camera systems for machine vision appl...
Chapter
The Fourier transform and the DFT are designed for processing complex-valued signals, and they always produce a complex-valued spectrum even in the case where the original signal was strictly realvalued. The reason is that neither the real nor the imaginary part of the Fourier spectrum alone is sufficient to represent (i.e., reconstruct) the signal...
Chapter
In the discussion of the median filter in Chapter 5 (Sec. 5.4.2), we noticed that this type of filter can somehow alter 2D image structures. Figure 9.1 illustrates once more how corners are rounded off, holes of a certain size are filled, and small structures, such as single dots or thin lines, are removed. The median filter thus responds selective...
Chapter
The Fourier transform is defined not only for 1D signals but for functions of arbitrary dimension. Thus, 2D images are nothing special from a mathematical point of view.
Chapter
Although techniques based on binary image regions have been used for a very long time, they still play a major role in many practical image processing applications today because of their simplicity and efficiency. To obtain a binary image, the first and perhaps most critical step is to convert the initial grayscale (or color) image to a binary imag...
Chapter
Prominent image “events” originating from local changes in intensity or color, such as edges and contours, are of high importance for the visual perception and interpretation of images. The perceived amount of information in an image appears to be directly related to the distinctiveness of the contained structures and discontinuities. In fact, edge...
Chapter
The correlation-based registration methods described in Chapter 23 are rigid in the sense that they provide for translation as the only form of geometric transformation and positioning is limited to whole pixel units. In this chapter we look at methods that are capable of registering a reference image under (almost) arbitrary geometric transformati...
Chapter
Point operations perform a modification of the pixel values without changing the size, geometry, or local structure of the image. Each new pixel value \(b\;=\;I^\prime(u,v)\) depends exclusively on the previous value \(a\;=\;I(u,v)\) at the same position and is thus independent from any other pixel value, in particular from any of its neighboring p...
Chapter
In a binary image, pixels can take on exactly one of two values. These values are often thought of as representing the “foreground” and “background” in the image, even though these concepts often are not applicable to natural scenes. In this chapter we focus on connected regions in images and how to isolate and describe such structures.
Book
This modern, self-contained textbook provides an accessible introduction to the field from the perspective of a practicing programmer, supporting a detailed presentation of the fundamental concepts and techniques with practical exercises and fully worked out implementation examples. This much-anticipated new edition of the definitive textbook on Di...
Research
Full-text available
Supplementary book chapter (8) to Wilhelm Burger and Mark J. Burge, "Principles of Digital Image Processing - Advanced Methods (Vol. 3)", Undergraduate Topics in Computer Science, Springer-Verlag, London (2013).
Research
Full-text available
Dieses Dokument enthält eine relativ detaillierte algorithmische Darstellung der Erzeugung von ein- und mehrdimensionalem Gradientenrauschen unter besonderer Berücksichtigung der Methode von Perlin. Key terms: Gradient noise, multi-dimensional noise function, Perlin noise, image synthesis, algorithm, integer hash function, Java, ImageJ
Chapter
Die Fouriertransformation und die DFT sind für die Verarbeitung komplexwertiger Signale ausgelegt und erzeugen immer ein komplexwertiges Spektrum, auch wenn das ursprüngliche Signal ausschließlich reelle Werte aufweist. Der Grund dafür ist, dass weder der reelle noch der imaginäre Teil des Spektrums allein ausreicht, um das Signal vollständig darst...
Chapter
Eckpunkte sind markante strukturelle Ereignisse in einem Bild und daher in einer Reihe von Anwendungen nützlich, wie z.B. beim Verfolgen von Elementen in aufeinander folgenden Bildern (tracking), bei der Zuordnung von Bildstrukturen in Stereoaufnahmen, als Referenzpunkte zur geometrischen Vermessung, Kalibrierung von Kamerasystemen usw. Eckpunkte s...
Chapter
Allen bisher besprochenen Bildoperationen, also Punkt- und Filteroperationen, war gemeinsam, dass sie zwar die Intensitätsfunktion verändern, die Geometrie des Bilds jedoch unverändert bleibt. Durch geometrische Operationen werden Bilder verformt, d. h., Pixelwerte können ihre Position verändern. Typische Beispiele sind etwa eine Verschiebung oder...
Chapter
Obwohl die Methoden zur Verarbeitung von Binärbildern zu den ältesten überhaupt gehören, spielen sie auch heute noch wegen ihrer Einfachheit und Effizienz eine bedeutende Rolle. Um überhaupt ein Binärbild zu erhalten, ist der erste und vielleicht auch empfindlichste Schritt die Konvertierung des ursprünglichen Grau- oder Farbbilds in Schwarz/Weiß-W...
Chapter
Lange Zeit war die digitale Verarbeitung von Bildern einer relativ kleinen Gruppe von Spezialisten mit teurer Ausstattung und einschlägigen Kenntnissen vorbehalten. Spätestens durch das Auftauchen von digitalen Kameras, Scannern und Multi-Media-PCs auf den Schreibtischen vieler Zeitgenossen wurde jedoch die Beschäftigung mit digitalen Bildern, bewu...
Chapter
Farbbilder spielen in unserem Leben eine wichtige Rolle und sind auch in der digitalen Welt allgegenwärtig, ob im Fernsehen, in der Fotografie oder im digitalen Druck. Die Empfindung von Farbe ist ein faszinierendes und gleichzeitig kompliziertes Phänomen, das Naturwissenschaftler, Psychologen, Philosophen und Künstler seit Jahrhunderten beschäftig...
Chapter
In Kap. 6 haben wir gezeigt, wie man mithilfe von geeigneten Filtern Kanten finden kann, indem man an jeder Bildposition die Kantenstärke und möglicherweise auch die Orientierung der Kante bestimmt. Der darauf folgende Schritt bestand in der Entscheidung (z.B. durch Anwendung einer Schwellwertoperation auf die Kantenstärke), ob an einer Bildpositio...
Chapter
In den folgenden drei Kapiteln geht es um die Darstellung und Analyse von Bildern im Frequenzbereich, basierend auf der Zerlegung von Bildsignalen in so genannte harmonische Funktionen, also Sinus- und Kosinusfunktionen, mithilfe der bekannten Fouriertransformation. Das Thema wird wegen seines etwas mathematischen Charakters oft als schwierig empfu...
Chapter
Die in Kap. 23 gezeigten korrelationsbasierten Methoden zur Bildregistrierung sind starr in dem Sinn, dass sie nur die Translation als einzige Form der geometrischen Transformation zulassen und die Positionierung auf ganze Pixelschritte beschränkt ist. In diesem Kapitel befassen wir uns mit Methoden, die imstande sind, die Übereinstimmung eines Ref...
Chapter
Das Problem der Farbquantisierung besteht in der Auswahl einer beschränkten Menge von Farben zur möglichst getreuen Darstellung eines ursprünglichen Farbbilds. Stellen Sie sich vor, Sie wären ein Künstler und hätten gerade mit 150 unterschiedlichen Farbstiften eine Illustration mit den wunderbarsten Farbübergängen geschaffen. Einem Verleger gefällt...
Chapter
Wenn wir Bilder miteinander vergleichen, stellt sich die grundlegende Frage: Wann sind zwei Bilder gleich oder wie kann man deren Ähnlichkeit messen? Natürlich könnte man einfach definieren, dass zwei Bilder I 1 und I 2 genau dann gleich sind, wenn alle ihre Bildwerte identisch sind bzw. wenn – zumindest für IntensitÄtsbilder – die Differenz I 1−I...
Chapter
Die Fouriertransformation ist natürlich nicht nur für eindimensionale Signale definiert, sondern für Funktionen beliebiger Dimension, und somit sind auch zweidimensionale Bilder aus mathematischer Sicht nichts Besonderes.
Chapter
Kanteninformation ist die Grundlage vieler Anwendungen der der digitalen Bildverarbeitung und in Computer Vision, daher ist die zuverlässige Lokalisierung und Charakterisierung von Kanten eine wichtige Aufgabe. Grundlegende Methoden für die Kantendetektion in Grauwertbildern wurden bereits in Kap. 6 dargestellt. Farbbilder enthalten bei gleicher Au...
Chapter
Die wesentliche Eigenschaft der im vorigen Kapitel behandelten Punktoperationen war, dass der neue Wert eines Bildelements ausschließlich vom ursprünglichen Bildwert an derselben Position abhängig ist. Filter sind Punktoperationen dahingehend ähnlich, dass auch hier eine 1:1-Abbildung der Bildkoordinaten besteht, d. h., dass sich die Geometrie des...
Chapter
Für Anwendungen, die eine präzise, reproduzierbare und geräteunabhängige Darstellung von Farben erfordern, ist die Verwendung kalibrierter Farbsysteme unumgänglich. Diese Notwendigkeit ergibt sich z.B. in der gesamten Bearbeitungskette beim digitalen Farbdruck, aber auch bei der digitalen Filmproduktion oder bei Bilddatenbanken. Erfahrungsgemäß ist...
Chapter
Markante „Ereignisse“ in einem Bild, wie Kanten und Konturen, die durch lokale Veränderungen der Intensität oder Farbe zustande kommen, sind für die visuelle Wahrnehmung und Interpretation von Bildern von höchster Bedeutung. Die subjektive „Schärfe“ eines Bilds steht in direktem Zusammenhang mit der Ausgeprägtheit der darin enthaltenen Diskontinuit...
Chapter
Histogramme sind Bildstatistiken und ein häufig verwendetes Hilfsmittel, um wichtige Eigenschaften von Bildern rasch zu beurteilen. Insbesondere sind Belichtungsfehler, die bei der Aufnahme von Bildern entstehen, im Histogramm sehr leicht zu erkennen. Moderne Digitalkameras bieten durchwegs die Möglichkeit, das Histogramm eines gerade aufgenommenen...
Chapter
Bis vor wenigen Jahren war die Bildverarbeitungs-“Community“ eine relativ kleine Gruppe von Personen, die entweder Zugang zu teuren Bildverarbeitungswerkzeugen hatte oder – aus Notwendigkeit – damit begann, eigene Softwarepakete für die digitale Bildverarbeitung zu programmieren. Meistens begannen solche „Eigenbau“-Umgebungen mit kleinen Programmko...
Chapter
Die Anwendung von Filteroperationen auf Farbbilder ist ein häufiger Vorgang, von dem man zunächst meinen könnte, dass er kaum besondere Aufmerksamkeit verlangt. In diesem Kapitel zeigen wir, wie klassische lineare und nichtlineare Filter, die im Kontext von Grauwertbildern (siehe Kap.5) bereits ausführlich behandelt wurden, entweder direkt oder in...
Chapter
Bei der Diskussion des Medianfilters in Kap. 5 konnten wir sehen, dass dieser Typ von Filter in der Lage ist, zweidimensionale Bildstrukturen zu verändern (Abschn. 5.4.2). Interessant war zum Beispiel, dass Ecken abgerundet werden und kleinere Strukturen, wie einzelne Punkte und dünne Linien, infolge der Filterung überhaupt verschwinden können (Abb...
Chapter
Viele praktische Anwendungen erfordern die Lokalisierung von Referenzpositionen in einem oder mehreren Bildern, beispielsweise zur Korrektur von Verzerrungen, für das Alignment von Bildern, die Verfolgung von Bildobjekten oder für die 3D-Rekonstruktion. Wir haben u. a. in Kap. 7 gesehen, dass Eckpunkte in Bildern recht zuverlässig und unabhängig vo...
Chapter
Als Interpolation bezeichnet man den Vorgang, die Werte einer diskreten Funktion für Positionen abseits ihrer Stützstellen zu schätzen. Bei geometrischen Bildoperationen ergibt sich diese Aufgabenstellung aus dem Umstand, dass durch die geometrische Abbildung T (bzw. T −1) diskrete Rasterpunkte im Allgemeinen nicht auf diskrete Bildpositionen im je...
Chapter
Als Punktoperationen bezeichnet man Operationen auf Bilder, die nur die Werte der einzelnen Bildelemente betreffen und keine Änderungen der Größe, Geometrie oder der lokalen Bildstruktur nach sich ziehen. Jeder neue Pixelwert b ist ausschließlich abhängig vom ursprünglichen Pixelwert a = I(u, v) an der selben Position und damit unabhängig von den W...
Chapter
Die Reduktion von Bildrauschen ist eine häufige Aufgabe in der digitalen Bildverarbeitung, nicht nur zur visuellen Verbesserung von Bildern sondern auch zur Vereinfachung der Bildanalyse, etwa der nachfolgenden Segmentierung oder der Extraktion von Objekten. Einfache Glättungsfilter wie das Gaußfilter sind Tiefpassfilter, die hochfrequentes Bildrau...
Chapter
Binärbilder, mit denen wir uns bereits im vorhergehenden Kapitel ausführlich beschäftigt haben, sind Bilder, in denen ein Pixel einen von nur zwei Werten annehmen kann. Wir bezeichnen diese beiden Werte häufig als „Vordergrund“ bzw. „Hintergrund“, obwohl eine solche eindeutige Unterscheidung in natürlichen Bildern oft nicht möglich ist. In diesem K...
Chapter
Many real applications require the localization of reference positions in one or more images, for example, for image alignment, removing distortions, object tracking, 3D reconstruction etc. We have seen that corner points can be located quite reliably and independent to orientation. However, typical corner detectors only provide the position and st...
Chapter
Color images are everywhere and filtering them is such a common task that it does not seem to require much attention at all. In this chapter, we describe how classical linear and non-linear filters, which we covered before in the context of grayscale images, can be either used directly or adapted for the processing of color images. Often color imag...
Chapter
Although techniques based on binary image regions have been used for a very long time, they still play a major role in many practical image processing applications today because of their simplicity and efficiency. To obtain a binary image, the first and perhaps most critical step is to convert the initial grayscale (or color) image to a binary imag...
Chapter
Fourier descriptors are an interesting method for modeling 2D shapes that are described as closed contours. Unlike polylines or splines, which are explicit and local descriptions of the contour, Fourier descriptors are global shape representations, i. e., each component stands for a particular characteristic of the entire shape. If one component is...
Chapter
Noise reduction in images is a common objective in image processing, not only for producing pleasing results for human viewing but also to facilitate easier extraction of meaningful information in subsequent steps, for example, in segmentation or feature detection. Simple smoothing filters, such as the Gaussian filter and the filters discussed in C...
Chapter
Edge information is essential in many image analysis and computer vision applications and thus the ability to locate and characterize edges robustly and accurately is an important task. Basic techniques for edge detection in grayscale images are discussed in Chapter 6 of Volume 1 [20]. Color images contain richer information than grayscale images a...
Chapter
This third volume in the authors’ Principles of Digital Image Processing series presents a thoughtful selection of advanced topics. Unlike our first two volumes, this one delves deeply into a select set of advanced and largely independent topics. Each of these topics is presented as a separate module which can be understood independently of the oth...
Chapter
Full-text available
The aim of this chapter is to expose the underlying concepts of Perlin noise in a concise and accessible way and to show the necessary steps towards the implementation of 1-, 2- and N-dimensional noise functions. The algorithms described here should be easy to implement in any suitable programming language and a prototypical implementation in Java...
Conference Paper
Full-text available
This paper describes a method and implementation for removing global, repetitive 2D artifacts in images by interactively editing their Fourier spectra. Based on this concept, ldquoInSpectralrdquo is an interactive software application that provides intuitive and easy-to-use image editing functionality in the spectral domain with immediate visual fe...

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