AAS 204th Meeting, June 2004
Session 7 A Walk Through the HR Diagram
Poster, Monday, May 31, 2004, 9:20am-6:30pm, Ballroom

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[7.18] An Algorithm for Segmenting Speckle Images Taken with Large Format CCDs and Application to Binary Star Observations

H. Riedel, E. P. Horch (UMass Dartmouth), W. F. van Altena (Yale U.)

The UMD-Yale speckle group uses speckle imaging to determine orbits and stellar masses of binary systems. The group currently uses a special optics instrument called RYTSI (the RIT-Yale Tip-tilt Speckle Imager). This instrument is capable of taking images of speckle patterns at a sufficient speed for the analysis. This is done by placing an array of speckle patterns on the CCD-area with the help of moveable tip-tilt mirrors. The CCD camera systems used are a Kodak front illuminated CCD on loan from Rochester Institute of Technology (RIT) and more recently the MiniMosaic camera, a high-sensitivity facility CCD imager at Kitt Peak National Observatory, Arizona.

The design and application of an image segmentation software called “Imseg” has recently been completed. It processes FITS-images taken with the 3.5m WIYN telescope at Kitt Peak National Observatory, AZ. The “Imseg” software prepares the FITS images for further processing with the autocorrelation software in order to get a reconstructed image of a binary star system. The method is described and some data sets taken with the RIT CCD or the MiniMosaic CCD that have been processed by the “Imseg” software and analyzed by the autocorrelation software will also be shown. One of these sets taken with the MiniMosaic shows a reconstructed image of a binary system consisting of two magnitude 11 stars, which is a promising result for further speckle analysis. This work is funded by NSF Grant AST-0307450.

The WIYN Observatory is a joint facility of the University of Wisconsin-Madison, Indiana University, Yale University, and the National Optical Astronomy Observatories.


The author(s) of this abstract have provided an email address for comments about the abstract: u_hriedel@umassd.edu

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