A method for spatial deconvolution of spectra is presented. It follows the same fundamental principles as the "" MCS image deconvolution algorithm ÏÏ recently developed by Magain, Courbin, & Sohy and uses information contained in the spectrum of a reference point-spread function to spatially deconvolve spectra of very blended sources. An improved resolution rather than an inÐnite one is aimed at, overcoming the well-known problem of "" deconvolution artifacts.ÏÏ As in the MCS algorithm, the data are decomposed into a sum of analytical point sources and a numerically deconvolved background so that the spectrum of extended sources in the immediate vicinity of bright point sources may be accurately extracted and sharpened. The algorithm has been tested on simulated data including seeing variation as a function of wavelength and atmospheric refraction. It is shown that the spectra of severely blended point sources can be resolved while fully preserving the spectrophotometric properties of the data. Extended objects "" hidden ÏÏ by bright point sources (up to 4È5 mag brighter) can be accurately recovered as well, provided the data have a sufficiently high total signal-to-noise ratio (200È300 per spectral resolution element). Such spectra are relatively easy to obtain, even down to faint magnitudes, within a few hours of integration time with 10 m class telescopes.
For each minute of test, we computed: • mean reaction time • percentage of lapses (lapse = RT > 2s or no answer)• level of somnolence (determined by our system). EVALUATION OF THE PERFORMANCE OF AN EXPERIMENTAL SOMNOLENCE QUANTIFICATION SYSTEM IN TERMS OF REACTION TIMES AND LAPSESSomnolence is known to be a major cause of various types of accidents [1], and ocular parameters are recognized to be reliable physiological indicators of somnolence [2]. We have thus developed an experimental somnolence quantification system that uses images of the eye to automatically determine a level of somnolence on a numerical scale. The aim of this study is to show that the level of somnolence determined by our system is well related to the level of performance of subjects accomplishing three reaction-time tests in different sleep deprivation conditions.• 27 participants (12 M, 15 F, mean age of 24.3 years, range of 19-32 years)• Test = reaction time (RT) test (duration of 15 minutes) • Approved by ethics committee.• Région Wallonne (Belgium): for financial support;• Sleep Laboratory (CETES), University Hospital of Liège (Belgium): for expertise, assistance, and use of facilities.The level of somnolence determined by our system based on images of the eye is well "correlated" with the level of performance of a subject accomplishing a task. We have indeed shown that, in the case of a reaction-time task,• mean reaction times and percentages of lapses increased with levels of somnolence determined by our system; • a threshold of 5 on our scale of somnolence (from 0 to 10) is the best for predicting lapses. Our somnolence quantification system has thus significant potential for predicting performance decrements due to somnolence and, ultimately, for preventing somnolence-related accidents.
Les images scintigraphiques sont fortement affectées par du bruit poissonnien. Cet article présente les résultats d'une comparaison de débruiteurs de bruit poissonnien selon différents critères : le gain en rapport signal-sur-bruit, la préservation de la résolution et du contraste, et la qualité visuelle. Les techniques en ondelettes récentes pour débruiter un bruit poissonnien se répartissent en deux classes, basées sur : (1) la représentation de Haar, (2) la transformation du bruit poissonnien en bruit gaussien blanc par la transformée de Haar-Fisz suivie d'un débruitage. Trois variantes de la première classe et trois de la deuxième intégrant le filtre adaptatif de Wiener, quatre types de seuillage en ondelettes et la méthode bayesienne de Pizurica ont été comparées aux filtres de Metz et de Hanning et à Shine, un procédé systématique d'élimination de bruit. Toutes ces méthodes, excepté Shine, sont paramétriques. Pour chacune d'elles, des domaines de valeurs optimales des paramètres ont été mis en évidence en fonction des critères précités. Comme l'intersection de ces domaines était vide pour les méthodes en ondelettes sans seuillage, elles n'ont pas été comparées quantitativement. Les techniques de seuillage et Shine ont donné les meilleurs résultats en terme de résolution et de contraste. La meilleure amélioration en rapport signal-surbruit a été obtenue par les filtres. Idéalement, ceux-ci doivent être précisément définis pour chaque image, ce qui est difficile dans le contexte clinique. En outre, ils génèrent des artefacts sous forme d'oscillations. Par ailleurs, les techniques en ondelettes, assez lentes, n'ont pas apporté d'améliorations significatives. Ainsi, Shine, rapide et automatique, apparaît être une alternative intéressante.
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