Présentation d'un démonstrateur de synthèse d'ouverture utilisant des liaisons par fibres optiques

Nous présentons un ensemble complet d'aquisition et de traitement de données interférométriques. Le dispositif expérimental de synthèse d'ouverture, testé sur un objet de laboratoire, inclut des liaisons par fibres optiques permettant le transport cohérent des faisceaux. Ce dispositif a été utilisé pour une première évaluation de diverses méthodes de reconstruction d'image

WFPC2 Observations of Compact Star Cluster Nuclei in Low Luminosity Spiral Galaxies

We have used the Wide Field Planetary Camera 2 aboard the Hubble Space Telescope to image the compact star cluster nuclei of the nearby, late-type, low-luminosity spiral galaxies NGC 4395, NGC 4242, and ESO 359-029. We also analyze archival WFPC2 observations of the compact star cluster nucleus of M33. A comparative analysis of the structural and photometric properties of these four nuclei is presented. All of the nuclei are very compact, with luminosity densities increasing at small radii to the resolution limit of our data. NGC 4395 contains a Seyfert 1 nucleus with a distinct bipolar structure and bright associated filaments which are likely due to [OIII] emission. The M33 nucleus has a complex structure, with elongated isophotes and possible signatures of weak activity, including a jet-like component. The other two nuclei are not known to be active, but share similar physical size scales and luminosities to the M33 and NGC 4395 nuclei. The circumnuclear environments of all four of our program galaxies are extremely diffuse, have only low-to-moderate star formation, and appear to be devoid of large quantities of dust. The central gravitational potentials of the galaxies are also quite shallow, making the origin of these types of `naked' nuclei problematic.Comment: to appear in the July 1999 Astronomical Journal; 38 pages (Latex), 5 tables (postscript), 21 figures (gif); postscript versions of the figures may be obtained via anonymous ftp at ftp://ftp.cv.nrao.edu/NRAO-staff/lmatthew/lanl-nucle

Interactive Deconvolution with Error Analysis

Not Availabl

A Hybrid Multi-Neural Network Structure Optimization Handled by a Neurocomputer Complexity Estimator

International audienceno abstrac

A Modular Neural Classifier with Self-Organizing Learning: Performance Analysis

International audienceno abstrac

Alternative representations of an image via the 2D wavelet transform. Application to character recognition

Both in 1D (signal analysis) and 2D (image processing), the wavelet transform (WT) has become by now a standard tool. Although the discrete version, based on multiresolution analysis, is probably better known, the continous WT (CWT) plays a crucial role for the detection and analysis of particular features in a signal, and we will focus here on the latter. In 2D however, one faces a practical problem. Indeed, the full parameter space of the wavelet transform of an image is 4D. It yields a representation of the image in position parameters (range and perception angle), as well as scale and anisotropy angle. The real challenge is to compute and visualize the full continuous wavelet transform in all four variables--obviously a demanding task. Thus, in order to obtain a manageable tool, some of the variables must be frozen. In other words, one must limit oneself to sections of the parameter space, usually 2D or 3D. For 2D sections, two variables are fixed and the transform is viewed as a function of the two remaing ones, and similarly for 3D sections. Among the six possible 2D sections, two play a privileged role. They yield respectively the position representation, which is the standard one, and the scale-angle representation, which has been proposed and studied systematically by two of us in a number of works. In this paper we will review these results and investigate the four remaining 2D representations. We will also make some comments on possible applications of 3D sections. The most spectacular property of the CWT is its ability at detecting discontinuities in a signal. In an image, this means in particular the sharp boundary between two regions of different luminosity, that is, a contour or an edge. Even more prominent in the transform are the corners of a given contour, for instance the contour of a letter. In a second part, we will exploit this property of the CWT and describe how one may design an algorithm for automatic character recognition (here we obviously work in the position--range-perception angle--representation). Several examples will be exhibited, illustrating in particluar the robustness of the method in the presence of noise