Statistical properties of dust far-infrared emission

The description of the statistical properties of dust emission gives important constraints on the physics of the interstellar medium but it is also a useful way to estimate the contamination of diffuse interstellar emission in the cases where it is considered a nuisance. The main goals of this analysis of the power spectrum and non-Gaussian properties of 100 micron dust emission are 1) to estimate the power spectrum of interstellar matter density in three dimensions, 2) to review and extend previous estimates of the cirrus noise due to dust emission and 3) to produce simulated dust emission maps that reproduce the observed statistical properties. The main results are the following. 1) The cirrus noise level as a function of brightness has been previously overestimated. It is found to be proportional to instead of ^1.5, where is the local average brightness at 100 micron. This scaling is in accordance with the fact that the brightness fluctuation level observed at a given angular scale on the sky is the sum of fluctuations of increasing amplitude with distance on the line of sight. 2) The spectral index of dust emission at scales between 5 arcmin and 12.5 degrees is =-2.9 on average but shows significant variations over the sky. Bright regions have systematically steeper power spectra than diffuse regions. 3) The skewness and kurtosis of brightness fluctuations is high, indicative of strong non-Gaussianity. 4) Based on our characterization of the 100 micron power spectrum we provide a prescription of the cirrus confusion noise as a function of wavelength and scale. 5) Finally we present a method based on a modification of Gaussian random fields to produce simulations of dust maps which reproduce the power spectrum and non-Gaussian properties of interstellar dust emission.Comment: 13 pages, 13 figures. Accepted for publication in A&

Joint Planck and WMAP CMB Map Reconstruction

We present a novel estimate of the cosmological microwave background (CMB) map by combining the two latest full-sky microwave surveys: WMAP nine-year and Planck PR1. The joint processing benefits from a recently introduced component separation method coined "local-generalized morphological component analysis'' (LGMCA) based on the sparse distribution of the foregrounds in the wavelet domain. The proposed estimation procedure takes advantage of the IRIS 100 micron as an extra observation on the galactic center for enhanced dust removal. We show that this new CMB map presents several interesting aspects: i) it is a full sky map without using any inpainting or interpolating method, ii) foreground contamination is very low, iii) the Galactic center is very clean, with especially low dust contamination as measured by the cross-correlation between the estimated CMB map and the IRIS 100 micron map, and iv) it is free of thermal SZ contamination.Comment: Astronomy and Astrophysics, accepte

Predicted Planck Extragalactic Point Source Catalogue

An estimation of the number and amplitude (in flux) of the extragalactic point sources that will be observed by the Planck Mission is presented in this paper. The study is based on the Mexican Hat wavelet formalism introduced by Cayon et al. 2000. Simulations at Planck observing frequencies are analysed, taking into account all the possible cosmological, Galactic and Extragalactic emissions together with noise. With the technique used in this work the Planck Mission will produce a catalogue of extragalactic point sources above fluxes: 1.03 Jy (857 GHz), 0.53 Jy (545 GHz), 0.28 Jy (353 GHz), 0.24 Jy (217 GHz), 0.32 Jy (143 GHz), 0.41 Jy (100 GHz HFI), 0.34 Jy (100 GHz LFI), 0.57 Jy (70 GHz), 0.54 Jy (44 GHz) and 0.54 Jy (30 GHz), which are only slightly model dependent (see text). Amplitudes of these sources are estimated with errors below 15%. Moreover, we also provide a complete catalogue (for the point sources simulation analysed) with errors in the estimation of the amplitude below 10%. In addition we discuss the possibility of identifying different point source populations in the Planck catalogue by estimating their spectral indices.Comment: 13 pages, 2 figures, submitted to MNRA

Development and evaluation of image registration and segmentation algorithms for long wavelength infrared and visible wavelength images

In this thesis, algorithms for image registration and segmentation are developed to locate and identify DU penetrators and associated metal projectile debris on or near the surface at the US DoD firing ranges and proving grounds. The proposed registration algorithm supports fusing the LWIR and visible images. Control points are indentified by area-base detection and followed by eliminating outliers. Associated with bilinear interpolation, the gravity centers of control points are used to estimate the transformation parameters. The segmentation with a statistical detector is developed to improve the fusion result. The power spectrum density is invoked to extract and identify the image properties, and the probability of each pixel classified as target further the decision. The final result is consistent with the true vision and carries distinguished target information. The combination of registration and segmentation approaches can effectively orientate and investigate the target area

Development and evaluation of image registration and segmentation algorithms for long wavelength infrared and visible wavelength images

In this thesis, algorithms for image registration and segmentation are developed to locate and identify DU penetrators and associated metal projectile debris on or near the surface at the US DoD firing ranges and proving grounds. The proposed registration algorithm supports fusing the LWIR and visible images. Control points are indentified by area-base detection and followed by eliminating outliers. Associated with bilinear interpolation, the gravity centers of control points are used to estimate the transformation parameters. The segmentation with a statistical detector is developed to improve the fusion result. The power spectrum density is invoked to extract and identify the image properties, and the probability of each pixel classified as target further the decision. The final result is consistent with the true vision and carries distinguished target information. The combination of registration and segmentation approaches can effectively orientate and investigate the target area

Probability of detection analysis for infrared nondestructive testing and evaluation with applications including a comparison with ultrasonic testing

La fiabilité d'une technique d’Évaluation Non-Destructive (END) est l'un des aspects les plus importants dans la procédure globale de contrôle industriel. La courbe de la Probabilité de Détection (PdD) est la mesure quantitative de la fiabilité acceptée en END. Celle-ci est habituellement exprimée en fonction de la taille du défaut. Chaque expérience de fiabilité en END devrait être bien conçue pour obtenir l'ensemble de données avec une source valide, y compris la technique de Thermographie Infrarouge (TI). La gamme des valeurs du rapport de l'aspect de défaut (Dimension / profondeur) est conçue selon nos expériences expérimentales afin d’assurer qu’elle vient du rapport d’aspect non détectable jusqu’à celui-ci soit détectable au minimum et plus large ensuite. Un test préliminaire est mis en œuvre pour choisir les meilleurs paramètres de contrôle, telles que l'énergie de chauffage, le temps d'acquisition et la fréquence. Pendant le processus de traitement des images et des données, plusieurs paramètres importants influent les résultats obtenus et sont également décrits. Pour la TI active, il existe diverses sources de chauffage (optique ou ultrason), des formes différentes de chauffage (pulsé ou modulé, ainsi que des méthodes différentes de traitement des données. Diverses approches de chauffage et de traitement des données produisent des résultats d'inspection divers. Dans cette recherche, les techniques de Thermographie Pulsée (TP) et Thermographie Modulée(TM) seront impliquées dans l'analyse de PdD. Pour la TP, des courbes PdD selon différentes méthodes de traitement de données sont comparées, y compris la Transformation de Fourier, la Reconstruction du Signal thermique, la Transformation en Ondelettes, le Contraste Absolu Différentiel et les Composantes Principales en Thermographie. Des études systématiques sur l'analyse PdD pour la technique de TI sont effectuées. Par ailleurs, les courbes de PdD en TI sont comparées avec celles obtenues par d'autres approches traditionnelles d’END.The reliability of a Non-Destructive Testing and Evaluation (NDT& E) technique is one of the most important aspects of the overall industrial inspection procedure. The Probability of Detection (PoD) curve is the accepted quantitative measure of the NDT& E reliability, which is usually expressed as a function of flaw size. Every reliability experiment of the NDT& E system must be well designed to obtain a valid source data set, including the infrared thermography (IRT) technique. The range of defect aspect ratio (Dimension / depth) values is designed according to our experimental experiences to make sure it is from non-detectable to minimum detectable aspect ratio and larger. A preliminary test will be implemented to choose the best inspection parameters, such as heating energy, the acquisition time and frequency. In the data and image processing procedure, several important parameters which influence the results obtained are also described. For active IRT, there are different heating sources (optical or ultrasound), heating forms (pulsed or lock-in) and also data processing methods. Distinct heating and data processing manipulations produce different inspection results. In this research, both optical Pulsed Thermography (PT) and Lock-in Thermography (LT) techniques will be involved in the PoD analysis. For PT, PoD curves of different data processing methods are compared, including Fourier Transform (FT), 1st Derivative (1st D) after Thermal Signal Reconstruction (TSR), Wavelet Transform (WT), Differential Absolute Contrast (DAC), and Principal Component Thermography (PCT). Systematic studies on PoD analysis for IRT technique are carried out. Additionally, constructed PoD curves of IRT technique are compared with those obtained by other traditional NDT& E approaches

Face recognition by means of advanced contributions in machine learning

Face recognition (FR) has been extensively studied, due to both scientific fundamental challenges and current and potential applications where human identification is needed. FR systems have the benefits of their non intrusiveness, low cost of equipments and no useragreement requirements when doing acquisition, among the most important ones. Nevertheless, despite the progress made in last years and the different solutions proposed, FR performance is not yet satisfactory when more demanding conditions are required (different viewpoints, blocked effects, illumination changes, strong lighting states, etc). Particularly, the effect of such non-controlled lighting conditions on face images leads to one of the strongest distortions in facial appearance. This dissertation addresses the problem of FR when dealing with less constrained illumination situations. In order to approach the problem, a new multi-session and multi-spectral face database has been acquired in visible, Near-infrared (NIR) and Thermal infrared (TIR) spectra, under different lighting conditions. A theoretical analysis using information theory to demonstrate the complementarities between different spectral bands have been firstly carried out. The optimal exploitation of the information provided by the set of multispectral images has been subsequently addressed by using multimodal matching score fusion techniques that efficiently synthesize complementary meaningful information among different spectra. Due to peculiarities in thermal images, a specific face segmentation algorithm has been required and developed. In the final proposed system, the Discrete Cosine Transform as dimensionality reduction tool and a fractional distance for matching were used, so that the cost in processing time and memory was significantly reduced. Prior to this classification task, a selection of the relevant frequency bands is proposed in order to optimize the overall system, based on identifying and maximizing independence relations by means of discriminability criteria. The system has been extensively evaluated on the multispectral face database specifically performed for our purpose. On this regard, a new visualization procedure has been suggested in order to combine different bands for establishing valid comparisons and giving statistical information about the significance of the results. This experimental framework has more easily enabled the improvement of robustness against training and testing illumination mismatch. Additionally, focusing problem in thermal spectrum has been also addressed, firstly, for the more general case of the thermal images (or thermograms), and then for the case of facialthermograms from both theoretical and practical point of view. In order to analyze the quality of such facial thermograms degraded by blurring, an appropriate algorithm has been successfully developed. Experimental results strongly support the proposed multispectral facial image fusion, achieving very high performance in several conditions. These results represent a new advance in providing a robust matching across changes in illumination, further inspiring highly accurate FR approaches in practical scenarios.El reconeixement facial (FR) ha estat àmpliament estudiat, degut tant als reptes fonamentals científics que suposa com a les aplicacions actuals i futures on requereix la identificació de les persones. Els sistemes de reconeixement facial tenen els avantatges de ser no intrusius,presentar un baix cost dels equips d’adquisició i no la no necessitat d’autorització per part de l’individu a l’hora de realitzar l'adquisició, entre les més importants. De totes maneres i malgrat els avenços aconseguits en els darrers anys i les diferents solucions proposades, el rendiment del FR encara no resulta satisfactori quan es requereixen condicions més exigents (diferents punts de vista, efectes de bloqueig, canvis en la il·luminació, condicions de llum extremes, etc.). Concretament, l'efecte d'aquestes variacions no controlades en les condicions d'il·luminació sobre les imatges facials condueix a una de les distorsions més accentuades sobre l'aparença facial. Aquesta tesi aborda el problema del FR en condicions d'il·luminació menys restringides. Per tal d'abordar el problema, hem adquirit una nova base de dades de cara multisessió i multiespectral en l'espectre infraroig visible, infraroig proper (NIR) i tèrmic (TIR), sota diferents condicions d'il·luminació. En primer lloc s'ha dut a terme una anàlisi teòrica utilitzant la teoria de la informació per demostrar la complementarietat entre les diferents bandes espectrals objecte d’estudi. L'òptim aprofitament de la informació proporcionada pel conjunt d'imatges multiespectrals s'ha abordat posteriorment mitjançant l'ús de tècniques de fusió de puntuació multimodals, capaces de sintetitzar de manera eficient el conjunt d’informació significativa complementària entre els diferents espectres. A causa de les característiques particulars de les imatges tèrmiques, s’ha requerit del desenvolupament d’un algorisme específic per la segmentació de les mateixes. En el sistema proposat final, s’ha utilitzat com a eina de reducció de la dimensionalitat de les imatges, la Transformada del Cosinus Discreta i una distància fraccional per realitzar les tasques de classificació de manera que el cost en temps de processament i de memòria es va reduir de forma significa. Prèviament a aquesta tasca de classificació, es proposa una selecció de les bandes de freqüències més rellevants, basat en la identificació i la maximització de les relacions d'independència per mitjà de criteris discriminabilitat, per tal d'optimitzar el conjunt del sistema. El sistema ha estat àmpliament avaluat sobre la base de dades de cara multiespectral, desenvolupada pel nostre propòsit. En aquest sentit s'ha suggerit l’ús d’un nou procediment de visualització per combinar diferents bandes per poder establir comparacions vàlides i donar informació estadística sobre el significat dels resultats. Aquest marc experimental ha permès més fàcilment la millora de la robustesa quan les condicions d’il·luminació eren diferents entre els processos d’entrament i test. De forma complementària, s’ha tractat la problemàtica de l’enfocament de les imatges en l'espectre tèrmic, en primer lloc, pel cas general de les imatges tèrmiques (o termogrames) i posteriorment pel cas concret dels termogrames facials, des dels punt de vista tant teòric com pràctic. En aquest sentit i per tal d'analitzar la qualitat d’aquests termogrames facials degradats per efectes de desenfocament, s'ha desenvolupat un últim algorisme. Els resultats experimentals recolzen fermament que la fusió d'imatges facials multiespectrals proposada assoleix un rendiment molt alt en diverses condicions d’il·luminació. Aquests resultats representen un nou avenç en l’aportació de solucions robustes quan es contemplen canvis en la il·luminació, i esperen poder inspirar a futures implementacions de sistemes de reconeixement facial precisos en escenaris no controlats.Postprint (published version

Thermal and Visual Imaging and Accelerometry Developments to Assist with Arthritis Diagnosis

Juvenile Idiopathic Arthritis (JIA) is a disease that causes pain and inflammation in the joints of children. Its early diagnosis is important to avoid damage to the joints. Joint warmth, redness and movement restriction may be indicators of active arthritis hence accurate objective means to measure temperature, colour and range of movement (ROM) at the joint may assist diagnosis. In this study, three techniques with a potential to assist clinicians in diagnosing JIA were developed. These were based on high-resolution thermal imaging (HRTI), visual imaging and accelerometry. A detailed correlation analysis was performed between the developed methods and the consultant's clinical assessment of JIA diagnosis. Twenty-two patients (age: mean=10.6 years, SD = 2 years) with JIA diagnosis were recruited. 18 participated in the thermal/visual imaging study only, 2 in the accelerometry study only and 2 in both thermal/visual imaging and accelerometry studies. Thermal and visual images of the front and back of the knees and ankles of 20 patients were studied. All ethical approvals from Sheffield Hallam University and the National Health Service (NHS) were duly obtained before commencing the study. The thermal/visual imaging study involved developing image processing techniques to accurately identify and segment the regions of interest (ROIs). A tracking algorithm to accurately locate the ROIs was also implemented. An accelerometry system that is capable of recording movements from 4 channels was developed and its signals were processed by frequency spectrum analysis, short-time Fourier transform and wavelet packet analysis. The thermal imaging results showed a combined 71% correlation (for the front of knees and ankles) with clinical assessment. It may be possible that patients whom their arthritic joint was cooler than their healthy joints may have relied on their healthy leg more extensively for mobility (due to the pain on the arthritic leg) thus increasing its joints temperature. It was also found that JIA may affect the skin colour with a combined 42% correlation between the knees and ankles. The accelerometry results showed a 75% correlation with clinical assessment. The study for the first time brought together the three techniques of thermal imaging, visual imaging and accelerometry to assist with JIA diagnosis. The study demonstrated that the developed techniques have potential in assisting clinicians with JIA diagnosis. Improvements in timely diagnosis allow more effective treatment and can reduce the likelihood of joint damage in rheumatoid arthritis

Science with High Spatial Resolution Far-Infrared Data

The goal of this workshop was to discuss new science and techniques relevant to high spatial resolution processing of far-infrared data, with particular focus on high resolution processing of IRAS data. Users of the maximum correlation method, maximum entropy, and other resolution enhancement algorithms applicable to far-infrared data gathered at the Infrared Processing and Analysis Center (IPAC) for two days in June 1993 to compare techniques and discuss new results. During a special session on the third day, interested astronomers were introduced to IRAS HIRES processing, which is IPAC's implementation of the maximum correlation method to the IRAS data. Topics discussed during the workshop included: (1) image reconstruction; (2) random noise; (3) imagery; (4) interacting galaxies; (5) spiral galaxies; (6) galactic dust and elliptical galaxies; (7) star formation in Seyfert galaxies; (8) wavelet analysis; and (9) supernova remnants

Global Shipping Container Monitoring Using Machine Learning with Multi-Sensor Hubs and Catadioptric Imaging

We describe a framework for global shipping container monitoring using machine learning with multi-sensor hubs and infrared catadioptric imaging. A wireless mesh radio satellite tag architecture provides connectivity anywhere in the world which is a significant improvement to legacy methods. We discuss the design and testing of a low-cost long-wave infrared catadioptric imaging device and multi-sensor hub combination as an intelligent edge computing system that, when equipped with physics-based machine learning algorithms, can interpret the scene inside a shipping container to make efficient use of expensive communications bandwidth. The histogram of oriented gradients and T-channel (HOG+) feature as introduced for human detection on low-resolution infrared catadioptric images is shown to be effective for various mirror shapes designed to give wide volume coverage with controlled distortion. Initial results for through-metal communication with ultrasonic guided waves show promise using the Dynamic Wavelet Fingerprint Technique (DWFT) to identify Lamb waves in a complicated ultrasonic signal