Progressive transmission of pseudo-color images. Appendix 1: Item 4

The transmission of digital images can require considerable channel bandwidth. The cost of obtaining such a channel can be prohibitive, or the channel might simply not be available. In this case, progressive transmission (PT) can be useful. PT presents the user with a coarse initial image approximation, and then proceeds to refine it. In this way, the user tends to receive information about the content of the image sooner than if a sequential transmission method is used. PT finds application in image data base browsing, teleconferencing, medical and other applications. A PT scheme is developed for use with a particular type of image data, the pseudo-color or color mapped image. Such images consist of a table of colors called a colormap, plus a 2-D array of index values which indicate which colormap entry is to be used to display a given pixel. This type of image presents some unique problems for a PT coder, and techniques for overcoming these problems are developed. A computer simulation of the color mapped PT scheme is developed to evaluate its performance. Results of simulation using several test images are presented

Multivariat analyse som verktøy til forståelse og reduksjon av kompleksitet av matematiske modeller i systembiologi

In the area of systems biology, technologies develop very fast, which allows us to collect massive amounts of various data. The main interest of scientists is to receive an insight into the obtained data sets and discover their inherent properties. Since the data often are rather complex and intimidating equations may be required for modelling, data analysis can be quite challenging for the majority of bio-scientists who do not master advanced mathematics. In this thesis it is proposed to use multivariate statistical methods as a tool for understanding the properties of complex models used for describing biological systems. The methods of multivariate analysis employed in this thesis search for latent variables that form a basis of all processes in a system. This often reduces dimensions of the system and makes it easier to get the whole picture of what is going on. Thus, in this work, methods of multivariate analysis were used with a descriptive purpose in Papers I and IV to discover effects of input variables on a response. Often it is necessary to know a functional form that could have generated the collected data in order to study the behaviour of the system when one or another parameter is tuned. For this purpose, we propose the Direct Look-Up (DLU) approach that is claimed here to be a worthy alternative to the already existing fitting methods due to its high computational speed and ability to avoid many problems such as subjectivity, choice of initial values, local optima and so on (Papers II and III). Another aspect covered in this thesis is an interpretation of function parameters by the custom human language with the use of multivariate analysis. This would enable mathematicians and bio-scientists to understand each other when describing the same object. It was accomplished here by using the concept of a metamodel and sensory analysis in Paper IV. In Paper I, a similar approach was used even though the main focus of the paper was slightly different. The original aim of the article was to show the advantages of the multi-way GEMANOVA analysis over the traditional ANOVA analysis for certain types of data. However, in addition, the relationship between human profiling of data samples and function parameters was discovered. In situations when funds for conducting experiments are limited and it is unrealizable to study all possible parameter combinations, it is necessary to have a smart way of choosing a few but most representative conditions for a particular system. In Paper V Multi-level Binary Replacement design (MBR) was developed as such, which can also be used for searching for a relevant parameter range. This new design method was applied here in Papers II and IV for selection of samples for further analyses.Teknologiutviklingen innenfor systembiologien er nå så rask at det gir mulighet til å samle svært store datamengder på kort tid og til relativ lav pris. Hovedinteressen til forskerne er typisk å få innsikt i dataene og deres iboende egenskaper. Siden data kan være ganske komplekse og ofte beskrives ved kompliserte, gjerne ikke-lineære, funksjoner, kan dataanalyse være ganske utfordrende for mange bioforskere som ikke behersker avansert matematikk. I dette arbeidet er det foreslått å bruke multivariat statistisk analyse for å komme nærmere en forståelse av egenskapene av kompliserte modeller som blir brukt for å beskrive biologiske systemer. De multivariate metodene som er benyttet i denne avhandlingen søker etter latente variabler som utgjør en lineær basis og tilnærming til de komplekse prosessene i et system. Dermed kan man oppnå en forenkling av systemet som er lettere å tolke. I dette arbeidet ble multivariate analysemetoder brukt i denne beskrivende hensikten i Artikler (Papers) I og IV til å oppdage effekter av funksjonsparametre på egenskapene til komplekse matematiske modeller. Ofte er det nødvendig å finne en matematisk funksjon som kunne ha generert de innsamlede dataene for å studere oppførselen av systemet. Med den hensikt foreslår vi en metode for modelltilpasning ved DLU-metoden (the Direct Look-Up) som her påstås å være et verdifullt alternativ til de eksisterende estimeringsmetodene på grunn av høy fart og evne til å unngå typiske problemer som for eksempel subjektivitet, valg av initialverdier, lokale optima, m.m (Artikler II og III). Et annet aspekt dekket i denne avhandlingen er bruken av multivariat analyse til å gi tolking av matematiske funksjonsparametre ved hjelp av et dagligdags vokabular. Dette kan gjøre det enklere for matematikere og bioforskere å forstå hverandre når de beskriver det samme objektet. Det var utført her ved å benytte ideen om en metamodell og sensorisk analyse i Artikkel IV. I Artikkel I var en lignende metode også brukt for å få sensoriske beskrivelser av bilder generert fra differensiallikninger. Hovedfokuset i Artikkel I var imidlertid et annet, nemlig å vise fordelen ved multi-way GEMANOVA-analyse fremfor den tradisjonelle ANOVA-analysen for visse datatyper. I denne artikkelen ble GEMANOVA brukt til å avdekke sammenhengen mellom kompliserte kombinasjoner av funksjonsparametrene og bildedeskriptorer. I situasjoner der ressurser til å utføre eksperimenter er begrenset og det er umulig å prøve ut alle kombinasjoner av parametre, er det behov for metoder som kan bestemme et fåtall av parameterinnstillinger som er mest mulig representative for et bestemt system. I Artikkel V ble derfor Multi-level Binary Replacement (MBR) design utviklet som en sådan, og den kan også brukes for å søke etter et relevant parameterrom for datasimuleringer. Den nye designmetoden ble anvendt i Artikler II og IV for utvelgelse av parameterverdier for videre analyser

Visual scene recognition with biologically relevant generative models

This research focuses on developing visual object categorization methodologies that are based on machine learning techniques and biologically inspired generative models of visual scene recognition. Modelling the statistical variability in visual patterns, in the space of features extracted from them by an appropriate low level signal processing technique, is an important matter of investigation for both humans and machines. To study this problem, we have examined in detail two recent probabilistic models of vision: a simple multivariate Gaussian model as suggested by (Karklin & Lewicki, 2009) and a restricted Boltzmann machine (RBM) proposed by (Hinton, 2002). Both the models have been widely used for visual object classification and scene analysis tasks before. This research highlights that these models on their own are not plausible enough to perform the classification task, and suggests Fisher kernel as a means of inducing discrimination into these models for classification power. Our empirical results on standard benchmark data sets reveal that the classification performance of these generative models could be significantly boosted near to the state of the art performance, by drawing a Fisher kernel from compact generative models that computes the data labels in a fraction of total computation time. We compare the proposed technique with other distance based and kernel based classifiers to show how computationally efficient the Fisher kernels are. To the best of our knowledge, Fisher kernel has not been drawn from the RBM before, so the work presented in the thesis is novel in terms of its idea and application to vision problem

Blickpunktabhängige Computergraphik

Contemporary digital displays feature multi-million pixels at ever-increasing refresh rates. Reality, on the other hand, provides us with a view of the world that is continuous in space and time. The discrepancy between viewing the physical world and its sampled depiction on digital displays gives rise to perceptual quality degradations. By measuring or estimating where we look, gaze-contingent algorithms aim at exploiting the way we visually perceive to remedy visible artifacts. This dissertation presents a variety of novel gaze-contingent algorithms and respective perceptual studies. Chapter 4 and 5 present methods to boost perceived visual quality of conventional video footage when viewed on commodity monitors or projectors. In Chapter 6 a novel head-mounted display with real-time gaze tracking is described. The device enables a large variety of applications in the context of Virtual Reality and Augmented Reality. Using the gaze-tracking VR headset, a novel gaze-contingent render method is described in Chapter 7. The gaze-aware approach greatly reduces computational efforts for shading virtual worlds. The described methods and studies show that gaze-contingent algorithms are able to improve the quality of displayed images and videos or reduce the computational effort for image generation, while display quality perceived by the user does not change.Moderne digitale Bildschirme ermöglichen immer höhere Auflösungen bei ebenfalls steigenden Bildwiederholraten. Die Realität hingegen ist in Raum und Zeit kontinuierlich. Diese Grundverschiedenheit führt beim Betrachter zu perzeptuellen Unterschieden. Die Verfolgung der Aug-Blickrichtung ermöglicht blickpunktabhängige Darstellungsmethoden, die sichtbare Artefakte verhindern können. Diese Dissertation trägt zu vier Bereichen blickpunktabhängiger und wahrnehmungstreuer Darstellungsmethoden bei. Die Verfahren in Kapitel 4 und 5 haben zum Ziel, die wahrgenommene visuelle Qualität von Videos für den Betrachter zu erhöhen, wobei die Videos auf gewöhnlicher Ausgabehardware wie z.B. einem Fernseher oder Projektor dargestellt werden. Kapitel 6 beschreibt die Entwicklung eines neuartigen Head-mounted Displays mit Unterstützung zur Erfassung der Blickrichtung in Echtzeit. Die Kombination der Funktionen ermöglicht eine Reihe interessanter Anwendungen in Bezug auf Virtuelle Realität (VR) und Erweiterte Realität (AR). Das vierte und abschließende Verfahren in Kapitel 7 dieser Dissertation beschreibt einen neuen Algorithmus, der das entwickelte Eye-Tracking Head-mounted Display zum blickpunktabhängigen Rendern nutzt. Die Qualität des Shadings wird hierbei auf Basis eines Wahrnehmungsmodells für jeden Bildpixel in Echtzeit analysiert und angepasst. Das Verfahren hat das Potenzial den Berechnungsaufwand für das Shading einer virtuellen Szene auf ein Bruchteil zu reduzieren. Die in dieser Dissertation beschriebenen Verfahren und Untersuchungen zeigen, dass blickpunktabhängige Algorithmen die Darstellungsqualität von Bildern und Videos wirksam verbessern können, beziehungsweise sich bei gleichbleibender Bildqualität der Berechnungsaufwand des bildgebenden Verfahrens erheblich verringern lässt

Engineering Data Compendium. Human Perception and Performance, Volume 1

The concept underlying the Engineering Data Compendium was the product an R and D program (Integrated Perceptual Information for Designers project) aimed at facilitating the application of basic research findings in human performance to the design of military crew systems. The principal objective was to develop a workable strategy for: (1) identifying and distilling information of potential value to system design from existing research literature, and (2) presenting this technical information in a way that would aid its accessibility, interpretability, and applicability by system designers. The present four volumes of the Engineering Data Compendium represent the first implementation of this strategy. This is Volume 1, which contains sections on Visual Acquisition of Information, Auditory Acquisition of Information, and Acquisition of Information by Other Senses

The Origin of Nonradiative Heating/momentum in Hot Stars

The origin of nonradiative heating and momentum in the atmospheres of stars is studied. The similarities and differences between what occurs in the hot stars and what occurs in cool stars are emphasized. Key points in the theory are reviewed. Areas requiring new study are indicated