Transform texture classification

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Ocean Engineering, 1996.Includes bibliographical references (leaves 155-163).by Xiaoou Tang.Ph.D

Autofocus and Back-Projection in Synthetic Aperture Radar Imaging.

Spotlight-mode Synthetic Aperture Radar (SAR) imaging has received considerable attention due to its ability to produce high-resolution images of scene reflectivity. One of the main challenges in successful image recovery is the problem of defocusing, which occurs due to inaccuracies in the estimated round-trip delays of the transmitted radar pulses. The problem is most widely studied for far-field imaging scenarios with a small range of look angles since the problem formulation can be significantly simplified under the assumptions of planar wavefronts and one-dimensional defocusing. In practice, however, these assumptions are frequently violated. MultiChannel Autofocus (MCA) is a subspace-based approach to the defocusing problem that was originally proposed for far-field imaging, with a small range of look angles. A key motivation behind MCA is the observation that there exists a low-return region within the recovered image, due to the weak illumination near the edges of the antenna footprint. The strength of the MCA formulation is that it can be easily extended to more realistic scenarios with polar-format data, spherical wavefronts, and arbitrary terrain, due to its flexible linear-algebraic framework. The main aim of this thesis is to devise a more broadly effective autofocus approach by adopting MCA to the aforementioned scenarios. By forming the solution space in a domain where the defocusing effect is truly one-dimensional, we show that drastically improved restorations can be obtained for applications with small to fairly wide ranges of look angles. When the terrain topography is known, we utilize the versatile backprojection-based imaging methods in the model formulations for MCA to accurately account for the underlying geometry. The proposed extended MCA shows reductions in RMSE of up to 50% when the underlying terrain is highly elevated. We also analyze the effects of the filtering step, the amount of wave curvature, the shape of the terrain, and the flight path of the radar, on the reconstructed image via backprojection. Finally, we discuss the selection of low-return constraints and the importance of using terrain elevation within MCA formulation.PHDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/135868/1/zzon_1.pd

Recent Techniques for Regularization in Partial Differential Equations and Imaging

abstract: Inverse problems model real world phenomena from data, where the data are often noisy and models contain errors. This leads to instabilities, multiple solution vectors and thus ill-posedness. To solve ill-posed inverse problems, regularization is typically used as a penalty function to induce stability and allow for the incorporation of a priori information about the desired solution. In this thesis, high order regularization techniques are developed for image and function reconstruction from noisy or misleading data. Specifically the incorporation of the Polynomial Annihilation operator allows for the accurate exploitation of the sparse representation of each function in the edge domain. This dissertation tackles three main problems through the development of novel reconstruction techniques: (i) reconstructing one and two dimensional functions from multiple measurement vectors using variance based joint sparsity when a subset of the measurements contain false and/or misleading information, (ii) approximating discontinuous solutions to hyperbolic partial differential equations by enhancing typical solvers with l1 regularization, and (iii) reducing model assumptions in synthetic aperture radar image formation, specifically for the purpose of speckle reduction and phase error correction. While the common thread tying these problems together is the use of high order regularization, the defining characteristics of each of these problems create unique challenges. Fast and robust numerical algorithms are also developed so that these problems can be solved efficiently without requiring fine tuning of parameters. Indeed, the numerical experiments presented in this dissertation strongly suggest that the new methodology provides more accurate and robust solutions to a variety of ill-posed inverse problems.Dissertation/ThesisDoctoral Dissertation Mathematics 201

Multifrequency Aperture-Synthesizing Microwave Radiometer System (MFASMR). Volume 1

Background material and a systems analysis of a multifrequency aperture - synthesizing microwave radiometer system is presented. It was found that the system does not exhibit high performance because much of the available thermal power is not used in the construction of the image and because the image that can be formed has a resolution of only ten lines. An analysis of image reconstruction is given. The system is compared with conventional aperture synthesis systems

Échantillonnage Non Uniforme : Application aux filtrages et aux conversions CAN/CNA (Convertisseurs Analogique-Numérique et Numérique/Analogique) dans les télécommunications par satellite

La théorie de l'échantillonnage uniforme des signaux, développée en particulier par C. Shannon, est à l'origine du traitement numérique du signal. Depuis, de nombreux travaux ont été consacrés à l'échantillonnage non uniforme. Celui-ci permet, d'une part, de modéliser les imperfections des dispositifs d'échantillonnage uniforme. D'autre part, l'échantillonnage peut être effectué de manière délibérément non uniforme afin de bénéficier de propriétés particulières, notamment un assouplissement des conditions portant sur le choix de la fréquence moyenne d'échantillonnage. La plupart de ces travaux reste dans un cadre théorique en adoptant des schémas d'échantillonnage et des modèles de signaux simplifiés. Or, actuellement, dans de nombreux domaines d'application, tels que les communications par satellites, la conversion analogique-numérique s'effectue sous des contraintes fortes pour les largeurs de bande mises en jeu, en raison notamment des fréquences très élevées utilisées. Ces conditions opérationnelles accentuent les imperfections des dispositifs électroniques réalisant l'échantillonnage et induisent le choix de modèles de signaux et de schémas d'échantillonnage spécifiques. Cette thèse a pour objectif général d'identifier des modèles d'échantillonnage adaptés à ce cadre applicatif. Ceux-ci s'appliquent à des signaux aléatoires passe-bande, qui constituent un modèle classique en télécommunications. Ils doivent prendre en compte des facteurs technologiques, économiques ainsi que des contraintes bord de complexité et éventuellement intégrer des fonctionnalités propres aux télécommunications. La première contribution de cette thèse est de développer des formules d'échantillonnage non uniforme qui intègrent dans le domaine numérique des fonctionnalités délicates à implémenter dans le domaine analogique aux fréquences considérées. La deuxième contribution consiste à caractériser et à compenser les erreurs de synchronisation de dispositifs d'échantillonnage non uniforme particuliers, à savoir les convertisseurs analogique-numérique entrelacés temporellement, via des méthodes supervisées ou aveugles

Three Dimensional Bistatic Tomography Using HDTV

The thesis begins with a review of the principles of diffraction and reflection tomography; starting with the analytic solution to the inhomogeneous Helmholtz equation, after linearization by the Born approximation (the weak scatterer solution), and arriving at the Filtered Back Projection (Propagation) method of reconstruction. This is followed by a heuristic derivation more directly couched in the radar imaging context, without the rigor of the general inverse problem solution and more closely resembling an imaging turntable or inverse synthetic aperture radar. The heuristic derivation leads into the concept of the line integral and projections (the Radon Transform), followed by more general geometries where the plane wave approximation is invalid. We proceed next to study of the dependency of reconstruction on the space-frequency trajectory, combining the spatial aperture and waveform. Two and three dimensional apertures, monostatic and bistatic, fully and sparsely sampled and including partial apertures, with controlled waveforms (CW and pulsed, with and without modulation) define the filling of k-space and concomitant reconstruction performance. Theoretical developments in the first half of the thesis are applied to the specific example of bistatic tomographic imaging using High Definition Television (HDTV); the United States version of DVB-T. Modeling of the HDTV waveform using pseudonoise modulation to represent the hybrid 8VSB HDTV scheme and the move-stop-move approximation established the imaging potential, employing an idealized, isotropic 18 scatterer. As the move-stop-move approximation places a limitation on integration time (in cross correlation/pulse compression) due to transmitter/receiver motion, an exact solution for compensation of Doppler distortion is derived. The concept is tested with the assembly and flight test of a bistatic radar system employing software-defined radios (SDR). A three dimensional, bistatic collection aperture, exploiting an elevated commercial HDTV transmitter, is focused to demonstrate the principle. This work, to the best of our knowledge, represents a first in the formation of three dimensional images using bistatically-exploited television transmitters

Äänikentän tila-analyysi parametrista tilaäänentoistoa varten käyttäen harvoja mikrofoniasetelmia

In spatial audio capturing the aim is to store information about the sound field so that the sound field can be reproduced without a perceptual difference to the original. The need for this is in applications like virtual reality and teleconferencing. Traditionally the sound field has been captured with a B-format microphone, but it is not always a feasible solution due to size and cost constraints. Alternatively, also arrays of omnidirectional microphones can be utilized and they are often used in devices like mobile phones. If the microphone array is sparse, i.e., the microphone spacings are relatively large, the analysis of the sound Direction of Arrival (DoA) becomes ambiguous in higher frequencies. This is due to spatial aliasing, which is a common problem in narrowband DoA estimation. In this thesis the spatial aliasing problem was examined and its effect on DoA estimation and spatial sound synthesis with Directional Audio Coding (DirAC) was studied. The aim was to find methods for unambiguous narrowband DoA estimation. The current State of the Art methods can remove aliased estimates but are not capable of estimating the DoA with the optimal Time-Frequency resolution. In this thesis similar results were obtained with parameter extrapolation when only a single broadband source exists. The main contribution of this thesis was the development of a correlation-based method. The developed method utilizes pre-known, array-specific information on aliasing in each DoA and frequency. The correlation-based method was tested and found to be the best option to overcome the problem of spatial aliasing. This method was able to resolve spatial aliasing even with multiple sources or when the source’s frequency content is completely above the spatial aliasing frequency. In a listening test it was found that the correlation-based method could provide a major improvement to the DirAC synthesized spatial image quality when compared to an aliased estimator.Tilaäänen tallentamisessa tavoitteena on tallentaa äänikentän ominaisuudet siten, että äänikenttä pystytään jälkikäteen syntetisoimaan ilman kuuloaistilla havaittavaa eroa alkuperäiseen. Tarve tälle löytyy erilaisista sovelluksista, kuten virtuaalitodellisuudesta ja telekonferensseista. Perinteisesti äänikentän ominaisuuksia on tallennettu B-formaatti mikrofonilla, jonka käyttö ei kuitenkaan aina ole koko- ja kustannussyistä mahdollista. Vaihtoehtoisesti voidaan käyttää myös pallokuvioisista mikrofoneista koostuvia mikrofoniasetelmia. Mikäli mikrofonien väliset etäisyydet ovat liian suuria, eli asetelma on harva, tulee äänen saapumissuunnan selvittämisestä epäselvää korkeammilla taajuuksilla. Tämä johtuu ilmiöstä nimeltä tilallinen laskostuminen. Tämän diplomityön tarkoituksena oli tutkia tilallisen laskostumisen ilmiötä, sen vaikutusta saapumissuunnan arviointiin sekä tilaäänisynteesiin Directional Audio Coding (DirAC) -menetelmällä. Lisäksi tutkittiin menetelmiä, joiden avulla äänen saapumissuunta voitaisiin selvittää oikein myös tilallisen laskostumisen läsnä ollessa. Työssä havaittiin, että nykyiset ratkaisut laskostumisongelmaan eivät kykene tuottamaan oikeita suunta-arvioita optimaalisella aikataajuusresoluutiolla. Tässä työssä samantapaisia tuloksia saatiin laajakaistaisen äänilähteen tapauksessa ekstrapoloimalla suunta-arvioita laskostumisen rajataajuuden alapuolelta. Työn pääosuus oli kehittää korrelaatioon perustuva saapumissuunnan arviointimenetelmä, joka kykenee tuottamaan luotettavia arvioita rajataajuuden yläpuolella ja useamman äänilähteen ympäristöissä. Kyseinen menetelmä hyödyntää mikrofoniasetelmalle ominaista, saapumissuunnasta ja taajuudesta riippuvaista laskostumiskuviota. Kuuntelukokeessa havaittiin, että korrelaatioon perustuva menetelmä voi tuoda huomattavan parannuksen syntetisoidun tilaäänikuvan laatuun verrattuna synteesiin laskostuneilla suunta-arvioilla

Detection algorithms for spatial data

This dissertation addresses the problem of anomaly detection in spatial data. The problem of landmine detection in airborne spatial data is chosen as the specific detection scenario. The first part of the dissertation deals with the development of a fast algorithm for kernel-based non-linear anomaly detection in the airborne spatial data. The original Kernel RX algorithm, proposed by Kwon et al. [2005a], suffers from the problem of high computational complexity, and has seen limited application. With the aim to reduce the computational complexity, a reformulated version of the Kernel RX, termed the Spatially Weighted Kernel RX (SW-KRX), is presented. It is shown that under this reformulation, the detector statistics can be obtained directly as a function of the centered kernel Gram matrix. Subsequently, a methodology for the fast computation of the centered kernel Gram matrix is proposed. The key idea behind the proposed methodology is to decompose the set of image pixels into clusters, and expediting the computations by approximating the effect of each cluster as a whole. The SW-KRX algorithm is implemented for a special case, and comparative results are compiled for the SW-KRX vis-à-vis the RX anomaly detector. In the second part of the dissertation, a detection methodology for buried mine detection is presented. The methodology is based on extraction of color texture information using cross-co-occurrence features. A feature selection methodology based on Bhattacharya coefficients and principal feature analysis is proposed and detection results with different feature-based detectors are presented, to demonstrate the effectiveness of the proposed methodology in the extraction of useful discriminatory information --Abstract, page iii