@phdthesis{Muehlbauer2011,
  author    = {M{\"u}hlbauer, Felix},
  title     = {Entwurf, Methoden und Werkzeuge f{\"u}r komplexe Bildverarbeitungssysteme auf Rekonfigurierbaren System-on-Chip-Architekturen},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-59923},
  school      = {Universit{\"a}t Potsdam},
  year      = {2011},
  abstract  = {Bildverarbeitungsanwendungen stellen besondere Anspr{\"u}che an das ausf{\"u}hrende Rechensystem. Einerseits ist eine hohe Rechenleistung erforderlich. Andererseits ist eine hohe Flexibilit{\"a}t von Vorteil, da die Entwicklung tendentiell ein experimenteller und interaktiver Prozess ist. F{\"u}r neue Anwendungen tendieren Entwickler dazu, eine Rechenarchitektur zu w{\"a}hlen, die sie gut kennen, anstatt eine Architektur einzusetzen, die am besten zur Anwendung passt. Bildverarbeitungsalgorithmen sind inh{\"a}rent parallel, doch herk{\"o}mmliche bildverarbeitende eingebettete Systeme basieren meist auf sequentiell arbeitenden Prozessoren. Im Gegensatz zu dieser "Unstimmigkeit" k{\"o}nnen hocheffiziente Systeme aus einer gezielten Synergie aus Software- und Hardwarekomponenten aufgebaut werden. Die Konstruktion solcher System ist jedoch komplex und viele L{\"o}sungen, wie zum Beispiel grobgranulare Architekturen oder anwendungsspezifische Programmiersprachen, sind oft zu akademisch f{\"u}r einen Einsatz in der Wirtschaft. Die vorliegende Arbeit soll ein Beitrag dazu leisten, die Komplexit{\"a}t von Hardware-Software-Systemen zu reduzieren und damit die Entwicklung hochperformanter on-Chip-Systeme im Bereich Bildverarbeitung zu vereinfachen und wirtschaftlicher zu machen. Dabei wurde Wert darauf gelegt, den Aufwand f{\"u}r Einarbeitung, Entwicklung als auch Erweiterungen gering zu halten. Es wurde ein Entwurfsfluss konzipiert und umgesetzt, welcher es dem Softwareentwickler erm{\"o}glicht, Berechnungen durch Hardwarekomponenten zu beschleunigen und das zu Grunde liegende eingebettete System komplett zu prototypisieren. Hierbei werden komplexe Bildverarbeitungsanwendungen betrachtet, welche ein Betriebssystem erfordern, wie zum Beispiel verteilte Kamerasensornetzwerke. Die eingesetzte Software basiert auf Linux und der Bildverarbeitungsbibliothek OpenCV. Die Verteilung der Berechnungen auf Software- und Hardwarekomponenten und die daraus resultierende Ablaufplanung und Generierung der Rechenarchitektur erfolgt automatisch. Mittels einer auf der Antwortmengenprogrammierung basierten Entwurfsraumexploration ergeben sich Vorteile bei der Modellierung und Erweiterung. Die Systemsoftware wird mit OpenEmbedded/Bitbake synthetisiert und die erzeugten on-Chip-Architekturen auf FPGAs realisiert.},
  language  = {de}
}
@phdthesis{Semmo2016,
  author    = {Semmo, Amir},
  title     = {Design and implementation of non-photorealistic rendering techniques for 3D geospatial data},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-99525},
  school      = {Universit{\"a}t Potsdam},
  pages     = {XVI, 155},
  year      = {2016},
  abstract  = {Geospatial data has become a natural part of a growing number of information systems and services in the economy, society, and people's personal lives. In particular, virtual 3D city and landscape models constitute valuable information sources within a wide variety of applications such as urban planning, navigation, tourist information, and disaster management. Today, these models are often visualized in detail to provide realistic imagery. However, a photorealistic rendering does not automatically lead to high image quality, with respect to an effective information transfer, which requires important or prioritized information to be interactively highlighted in a context-dependent manner. Approaches in non-photorealistic renderings particularly consider a user's task and camera perspective when attempting optimal expression, recognition, and communication of important or prioritized information. However, the design and implementation of non-photorealistic rendering techniques for 3D geospatial data pose a number of challenges, especially when inherently complex geometry, appearance, and thematic data must be processed interactively. Hence, a promising technical foundation is established by the programmable and parallel computing architecture of graphics processing units. This thesis proposes non-photorealistic rendering techniques that enable both the computation and selection of the abstraction level of 3D geospatial model contents according to user interaction and dynamically changing thematic information. To achieve this goal, the techniques integrate with hardware-accelerated rendering pipelines using shader technologies of graphics processing units for real-time image synthesis. The techniques employ principles of artistic rendering, cartographic generalization, and 3D semiotics—unlike photorealistic rendering—to synthesize illustrative renditions of geospatial feature type entities such as water surfaces, buildings, and infrastructure networks. In addition, this thesis contributes a generic system that enables to integrate different graphic styles—photorealistic and non-photorealistic—and provide their seamless transition according to user tasks, camera view, and image resolution. Evaluations of the proposed techniques have demonstrated their significance to the field of geospatial information visualization including topics such as spatial perception, cognition, and mapping. In addition, the applications in illustrative and focus+context visualization have reflected their potential impact on optimizing the information transfer regarding factors such as cognitive load, integration of non-realistic information, visualization of uncertainty, and visualization on small displays.},
  language  = {en}
}
@phdthesis{Shekhar2023,
  author    = {Shekhar, Sumit},
  title     = {Image and video processing based on intrinsic attributes},
  doi       = {10.25932/publishup-62004},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-620049},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xii, 143},
  year      = {2023},
  abstract  = {Advancements in computer vision techniques driven by machine learning have facilitated robust and efficient estimation of attributes such as depth, optical flow, albedo, and shading. To encapsulate all such underlying properties associated with images and videos, we evolve the concept of intrinsic images towards intrinsic attributes. Further, rapid hardware growth in the form of high-quality smartphone cameras, readily available depth sensors, mobile GPUs, or dedicated neural processing units have made image and video processing pervasive. In this thesis, we explore the synergies between the above two advancements and propose novel image and video processing techniques and systems based on them. To begin with, we investigate intrinsic image decomposition approaches and analyze how they can be implemented on mobile devices. We propose an approach that considers not only diffuse reflection but also specular reflection; it allows us to decompose an image into specularity, albedo, and shading on a resource constrained system (e.g., smartphones or tablets) using the depth data provided by the built-in depth sensors. In addition, we explore how on-device depth data can further be used to add an immersive dimension to 2D photos, e.g., showcasing parallax effects via 3D photography. In this regard, we develop a novel system for interactive 3D photo generation and stylization on mobile devices. Further, we investigate how adaptive manipulation of baseline-albedo (i.e., chromaticity) can be used for efficient visual enhancement under low-lighting conditions. The proposed technique allows for interactive editing of enhancement settings while achieving improved quality and performance. We analyze the inherent optical flow and temporal noise as intrinsic properties of a video. We further propose two new techniques for applying the above intrinsic attributes for the purpose of consistent video filtering. To this end, we investigate how to remove temporal inconsistencies perceived as flickering artifacts. One of the techniques does not require costly optical flow estimation, while both provide interactive consistency control. Using intrinsic attributes for image and video processing enables new solutions for mobile devices - a pervasive visual computing device - and will facilitate novel applications for Augmented Reality (AR), 3D photography, and video stylization. The proposed low-light enhancement techniques can also improve the accuracy of high-level computer vision tasks (e.g., face detection) under low-light conditions. Finally, our approach for consistent video filtering can extend a wide range of image-based processing for videos.},
  language  = {en}
}