Browsing by Author "Groisman, G."

Now showing 1 - 3 of 3
  • Thumbnail Image
    ItemOpen Access
    AN APPROACH TO STELLAR PHOTOMETRY USING SIMULATED ANNEALING
    (1995-04-01) Parker, J.R.; Groisman, G.
    Simulated annealing can be quite effectively used to fit functions of many parameters to a set of data. This paper discusses the application of simulated annealing to the fitting of Moffat functions to crowded field star images. Overlapping star profiles can be fit simultaneously and missed stars can be located based on the $x sup 2$ value of the fit, and the resulting functional model yields excellent photometric results. This method has been integrated into a photometry system which allows the user to select the accuracy of the results at the expense of time needed to perform the calculations, and is but one example of such an application.
  • Thumbnail Image
    ItemOpen Access
    COMPUTER ASSISTED PHOTOMETRY USING SIMULATED ANNEALING
    (1993-02-01) Parker, J.R.; Groisman, G.
    The computationaltechnique known as simulated annealing, which originally was used to solve problems in combinatiorial optimization, can be quite effectively used to fit functions of many parameters to a set of data. This paper discusses the application of simulated annealing to the fitting of Moffat functions to crowded field star images. Overlapping star profiles can be fit simultaneously and missed stars can be located based on the $X sup 2$ value of the fit, and the resulting functional model yields excellent photometric results. This method has been integrated into a photometry system which allows the user to select the accuracy of the results at the expense of time needed to perform the calculations.
  • Thumbnail Image
    ItemOpen Access
    DATA MODELING IN SCIENTIFIC IMAGES USING SIMULATED ANNEALING
    (1993-02-01) Parker, J.R.; Groisman, G.
    One way to measure objects in some classes of scientific image is to model the objects by functions and then make the measurements on the functions. This works especially well for images that contain information in the form of relationships between grey level pixels. Here, the use of a Moffat function as a data model is explored, as is the use of simulated annealing to fit many instances of this function to the data in the image. Two examples are presented: stellar photometry, a natural application for the Moffat function, and reading DNA sequencing gels.