We describe mosaicing for a sequence of images acquired by a camera rotating about its centre. The novel contributions are in two areas. First, in the automation and estimation of image registration: images ( ) are registered under a full (8 degrees of freedom) homography; the registration is automatic and robust, and a maximum likelihood estimator is used. In particular the registration is con...

Abstract—We investigate a stochastic signal-processing framework for signals with sparse derivatives, where the samples of a Lévy process are corrupted by noise. The proposed signal model covers the well-known Brownian motion and piecewise-constant Poisson process; moreover, the Lévy family also contains other interesting members exhibiting heavy-tail statistics that fulfill the requirements of...

A Unified Method for the Measurement and Tracking of Narrowband Contacts from an Array of Sensors Robert E. Zarnich, Ph.D. George Mason University, 2000 Dissertation Director: Dr. Kristine L. Bell This dissertation describes a method in which the contact tracking and narrow band direction nding processes are treated as a joint estimation problem, as opposed to the conventional approach which tr...

BACKGROUND Near-infrared spectroscopy (NIRS) is a non-invasive neuroimaging technique that recently has been developed to measure the changes of cerebral blood oxygenation associated with brain activities. To date, for functional brain mapping applications, there is no standard on-line method for analysing NIRS data. METHODS In this paper, a novel on-line NIRS data analysis framework taking a...

The proposed model for noise-free data distribution play an important role for maximum a posteriori (MAP) estimator. Thus, in the wavelet based image denoising, it is necessary to select a proper model for distribution of wavelet coefficients. This paper presents a new image denoising algorithm based on the modeling of wavelet coefficients in each subband with a mixture of Gaussian probability ...

This study compares the performances of di erent methods for the di erentiation and localization of commonly encountered features in indoor environments. Di erentiation of such features is of interest for intelligent systems in a variety of applications such as system control based on acoustic signal detection and identi/cation, map building, navigation, obstacle avoidance, and target tracking....

The radio interface EDGE (Enhanced Data rates for Global Evolution) is currently being standardized as an evolutionary path from GSM and TDMA-IS136 for third-generation high-speed data wireless systems. For the EDGE system with multiple antennas, spatial-temporal equalization (STE) can reduce intersymbol interference and co-channel interference, thereby increasing the capacity and range. In thi...

We describe mosaicing for a sequence of images acquired by a camera rotating about its centre. The novel contributions are in two areas. First, in the automation and estimation of image registration: images (60+) are registered under a full (8 degrees of freedom) homography; the registration is automatic and robust, and a maximum likelihood estimator is used. In particular the registration is c...

The aim of this analysis is to explore the fundamental stability issues of a robotic vehicle carrying out localization, mapping, and feedback control in a perturbation-filled environment. Motivated by the application of an ocean vehicle performing an autonomous ship hull inspection, a planar vehicle model performs localization using point features from a given map. Cases in which the agent must...

Using first principles, we establish in this paper a connection between the maximum a posteriori (MAP) estimator and the variational formulation of optimizing a given functional subject to some noise constraints. A MAP estimator which uses a Markov or a maximum entropy random field model for a prior distribution can be viewed as a minimizer of a variational problem. Using notions from robust st...