Blind image quality assessment: from heuristic-based to learning-based

Image quality assessment (IQA) plays an important role in numerous digital image processing applications, including image compression, image transmission, and image restoration, etc. The goal of objective IQA is to develop computational models that can predict image quality in a way being consistent with human perception. Compared with subjective quality evaluations such as psycho-visual tests, objective IQA metrics have the advantages of predicting image quality automatically and effectively in a timely manner. This thesis focuses on a particular type of objective IQA – blind IQA (BIQA), where the developed methods not only achieve objective IQA, but also are able to assess the perceptual quality of digital images without access to their pristine reference counterparts. Firstly, a novel blind image sharpness evaluator is introduced in Chapter 3, which leverages the discrepancy measures of structural degradation. Secondly, a “completely blind” quality assessment metric for gamut-mapped images is designed in Chapter 4, which does not need subjective quality scores during the model training. Thirdly, a general-purpose BIQA method is presented in Chapter 5, which can evaluate the quality of digital images without prior knowledge on the types of distortions. Finally, in Chapter 6, a deep neural network-based general-purpose BIQA method is proposed, which is fully data driven and trained in an end-to-end manner. In summary, four BIQA methods are introduced in this thesis, where the first three are heuristic-based and the last one is learning-based. Unlike heuristics-based ones, the learning-based method does not involves manually engineered feature designs

A FRAMEWORK FOR CONCEPT VALIDATION IN DESIGN USING DIGITAL PROTOTYPING

Ph.DDOCTOR OF PHILOSOPH

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Data-driven approaches for interactive appearance editing

This thesis proposes several techniques for interactive editing of digital content and fast rendering of virtual 3D scenes. Editing of digital content - such as images or 3D scenes - is difficult, requires artistic talent and technical expertise. To alleviate these difficulties, we exploit data-driven approaches that use the easily accessible Internet data (e. g., images, videos, materials) to develop new tools for digital content manipulation. Our proposed techniques allow casual users to achieve high-quality editing by interactively exploring the manipulations without the need to understand the underlying physical models of appearance. First, the thesis presents a fast algorithm for realistic image synthesis of virtual 3D scenes. This serves as the core framework for a new method that allows artists to fine tune the appearance of a rendered 3D scene. Here, artists directly paint the final appearance and the system automatically solves for the material parameters that best match the desired look. Along this line, an example-based material assignment approach is proposed, where the 3D models of a virtual scene can be "materialized" simply by giving a guidance source (image/video). Next, the thesis proposes shape and color subspaces of an object that are learned from a collection of exemplar images. These subspaces can be used to constrain image manipulations to valid shapes and colors, or provide suggestions for manipulations. Finally, data-driven color manifolds which contain colors of a specific context are proposed. Such color manifolds can be used to improve color picking performance, color stylization, compression or white balancing.Diese Dissertation stellt Techniken zum interaktiven Editieren von digitalen Inhalten und zum schnellen Rendering von virtuellen 3D Szenen vor. Digitales Editieren - seien es Bilder oder dreidimensionale Szenen - ist kompliziert, benötigt künstlerisches Talent und technische Expertise. Um diese Schwierigkeiten zu relativieren, nutzen wir datengesteuerte Ansätze, die einfach zugängliche Internetdaten, wie Bilder, Videos und Materialeigenschaften, nutzen um neue Werkzeuge zur Manipulation von digitalen Inhalten zu entwickeln. Die von uns vorgestellten Techniken erlauben Gelegenheitsnutzern das Editieren in hoher Qualität, indem Manipulationsmöglichkeiten interaktiv exploriert werden können ohne die zugrundeliegenden physikalischen Modelle der Bildentstehung verstehen zu müssen. Zunächst stellen wir einen effizienten Algorithmus zur realistischen Bildsynthese von virtuellen 3D Szenen vor. Dieser dient als Kerngerüst einer Methode, die Nutzern die Feinabstimmung des finalen Aussehens einer gerenderten dreidimensionalen Szene erlaubt. Hierbei malt der Künstler direkt das beabsichtigte Aussehen und das System errechnet automatisch die zugrundeliegenden Materialeigenschaften, die den beabsichtigten Eigenschaften am nahesten kommen. Zu diesem Zweck wird ein auf Beispielen basierender Materialzuordnungsansatz vorgestellt, für den das 3D Model einer virtuellen Szene durch das simple Anführen einer Leitquelle (Bild, Video) in Materialien aufgeteilt werden kann. Als Nächstes schlagen wir Form- und Farbunterräume von Objektklassen vor, die aus einer Sammlung von Beispielbildern gelernt werden. Diese Unterräume können genutzt werden um Bildmanipulationen auf valide Formen und Farben einzuschränken oder Manipulationsvorschläge zu liefern. Schließlich werden datenbasierte Farbmannigfaltigkeiten vorgestellt, die Farben eines spezifischen Kontexts enthalten. Diese Mannigfaltigkeiten ermöglichen eine Leistungssteigerung bei Farbauswahl, Farbstilisierung, Komprimierung und Weißabgleich

A NUMERICAL STUDY OF A NEW SPRAY APPLICATOR

This study focuses on the design and development of a new spray applicator design utilizing effects of imposed pressure oscillations in conjunction with cavitation collapse energy to create distribution of fine droplets. An oscillating horn placed inside the nozzle performing high frequency oscillations is envisioned to provide the necessary pressure perturbations on the exiting liquid jet, while the nozzle geometry design in configured to amplify cavitation process. Initially, a two-zone approach modeling the nozzle interior and exterior in a separate fashion and later, a coupled strategy is proposed. Parametric studies describing the effect of horn stroke length, frequency, its position inside the nozzle in combination with different nozzle designs and liquid flow rates are explored to identify their contribution in obtaining desired cavitation characteristics. In this regard, incorporation of a backward facing step profile within the nozzle shows strong capability of generating the required cavitation and flow field distribution at the nozzle exit. The velocity modulations occuring at the nozzle exit due to oscillating horn structure result in a wide gamut of liquid structures specific to the imposed oscillation frequency and modulation amplitude. The disintegration characteristics of these modulated liquid jets are studied using a Volume-of-Fluid (VOF) interface capturing approach based on finite volume methodology employing an interface compression scheme. VOF methods are validated against experimental results and then subsequently used to study scaling parameters governing the modulated liquid jets. To perform coupled interior-exterior nozzle computations with cavitation, two new cavitation models are presented: First, a model based on Homogeneous Equilibrium assumptions for tracking cavitation events in a compressible framework is presented. Owing to its inability to simulate incompressible cavitating flows, a new cavitation event tracking model based on a Cavitation-Induced-Momentum-Defect (CIMD) correction approach is formulated utilizing a scalar transport model for vapor volume fraction with relevant transport, diffusion and source terms. Validations of both the models against experimental observations are detailed. Coupled internal-external liquid flow computations from the proposed atomizer design using a VOF-CIMD strategy shows strong potential for rapid drop formation in the presence of cavitation effects. A prototype model of a new spray applicator design is presented

Fuelling the zero-emissions road freight of the future: routing of mobile fuellers

The future of zero-emissions road freight is closely tied to the sufficient availability of new and clean fuel options such as electricity and Hydrogen. In goods distribution using Electric Commercial Vehicles (ECVs) and Hydrogen Fuel Cell Vehicles (HFCVs) a major challenge in the transition period would pertain to their limited autonomy and scarce and unevenly distributed refuelling stations. One viable solution to facilitate and speed up the adoption of ECVs/HFCVs by logistics, however, is to get the fuel to the point where it is needed (instead of diverting the route of delivery vehicles to refuelling stations) using "Mobile Fuellers (MFs)". These are mobile battery swapping/recharging vans or mobile Hydrogen fuellers that can travel to a running ECV/HFCV to provide the fuel they require to complete their delivery routes at a rendezvous time and space. In this presentation, new vehicle routing models will be presented for a third party company that provides MF services. In the proposed problem variant, the MF provider company receives routing plans of multiple customer companies and has to design routes for a fleet of capacitated MFs that have to synchronise their routes with the running vehicles to deliver the required amount of fuel on-the-fly. This presentation will discuss and compare several mathematical models based on different business models and collaborative logistics scenarios

Word Knowledge and Word Usage

Word storage and processing define a multi-factorial domain of scientific inquiry whose thorough investigation goes well beyond the boundaries of traditional disciplinary taxonomies, to require synergic integration of a wide range of methods, techniques and empirical and experimental findings. The present book intends to approach a few central issues concerning the organization, structure and functioning of the Mental Lexicon, by asking domain experts to look at common, central topics from complementary standpoints, and discuss the advantages of developing converging perspectives. The book will explore the connections between computational and algorithmic models of the mental lexicon, word frequency distributions and information theoretical measures of word families, statistical correlations across psycho-linguistic and cognitive evidence, principles of machine learning and integrative brain models of word storage and processing. Main goal of the book will be to map out the landscape of future research in this area, to foster the development of interdisciplinary curricula and help single-domain specialists understand and address issues and questions as they are raised in other disciplines