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1	Nonparametric Markov Random Field Models for Natural Texture Images Paget, Rupert Unknown Date (has links) The underlying aim of this research is to investigate the mathematical descriptions of homogeneous textures in digital images for the purpose of segmentation and recognition. The research covers the problem of testing these mathematical descriptions by using them to generate synthetic realisations of the homogeneous texture for subjective and analytical comparisons with the source texture from which they were derived. The application of this research is in analysing satellite or airborne images of the Earth's surface. In particular, Synthetic Aperture Radar (SAR) images often exhibit regions of homogeneous texture, which if segmented, could facilitate terrain classification. In this thesis we present noncausal, nonparametric, multiscale, Markov random field (MRF) models for recognising and synthesising texture. The models have the ability to capture the characteristics of, and to synthesise, a wide variety of textures, varying from the highly structured to the stochastic. For texture synthesis, we introduce our own novel multiscale approach incorporating a new concept of local annealing. This allows us to use large neighbourhood systems to model complex natural textures with high order statistical characteristics. The new multiscale texture synthesis algorithm also produces synthetic textures with few, if any, phase discontinuities. The power of our modelling technique is evident in that only a small source image is required to synthesise representative examples of the source texture, even when the texture contains long-range characteristics. We also show how the high-dimensional model of the texture may be modelled with lower dimensional statistics without compromising the integrity of the representation. We then show how these models -- which are able to capture most of the unique characteristics of a texture -- can be for the ``open-ended'' problem of recognising textures embedded in a scene containing previously unseen textures. Whilst this technique was developed for the practical application of recognising different terrain types from Synthetic Aperture Radar (SAR) images, it has applications in other image processing tasks requiring texture recognition. Markov Random Fields Gibbs Distributions Parametric Estimation Nonparametric Estimation Parzen Window Density
2	A Wide-Area Perspective on Power System Operation and Dynamics Gardner, Robert Matthew 23 April 2008 (has links) Classically, wide-area synchronized power system monitoring has been an expensive task requiring significant investment in utility communications infrastructures for the service of relatively few costly sensors. The purpose of this research is to demonstrate the viability of power system monitoring from very low voltage levels (120 V). Challenging the accepted norms in power system monitoring, the document will present the use of inexpensive GPS time synchronized sensors in mass numbers at the distribution level. In the past, such low level monitoring has been overlooked due to a perceived imbalance between the required investment and the usefulness of the resulting deluge of information. However, distribution level monitoring offers several advantages over bulk transmission system monitoring. First, practically everyone with access to electricity also has a measurement port into the electric power system. Second, internet access and GPS availability have become pedestrian commodities providing a communications and synchronization infrastructure for the transmission of low-voltage measurements. Third, these ubiquitous measurement points exist in an interconnected fashion irrespective of utility boundaries. This work offers insight into which parameters are meaningful to monitor at the distribution level and provides applications that add unprecedented value to the data extracted from this level. System models comprising the entire Eastern Interconnection are exploited in conjunction with a bounty of distribution level measurement data for the development of wide-area disturbance detection, classification, analysis, and location routines. The main contributions of this work are fivefold: the introduction of a novel power system disturbance detection algorithm; the development of a power system oscillation damping analysis methodology; the development of several parametric and non-parametric power system disturbance location methods, new methods of power system phenomena visualization, and the proposal and mapping of an online power system event reporting scheme. / Ph. D. TDOA FNET FDR GPS Wide-Area monitoring wide-area measurements power system event power system load shedding generation trip eastern interconnection wams ems nerc ercot wecc parzen window interconnection islanding PMU half-plane method least squares event trigger generation-load mismatch electromechanical wave wave propagation time delay of arrival oscillation trigger modal analysis electric grid transmission network transmission system hypocenter frequency matrix pencil mahalanobis distance

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Nonparametric Markov Random Field Models for Natural Texture Images

A Wide-Area Perspective on Power System Operation and Dynamics